DEV Community: Ashkan Rajaee

Cognizant Says Half Its Code Is AI-Assisted. Its Headcount Still Grew by 10,100.

Ashkan Rajaee — Mon, 02 Nov 2026 14:31:40 +0000

Cognizant reported its third quarter 2026 results on October 29. Revenue was $5.7 billion, up 4.6% year over year, or 4.8% in constant currency. CEO Ravi Kumar S said the company is moving through the AI shift with "over 50% of our code now AI-assisted" and "continued improvement in revenue and adjusted operating income per employee." Total headcount was 359,900 at the end of September, up 10,100 from a year earlier and up 3,200 from June. In one client example, Cognizant said a seven-person team used Devin, Cognition's AI software engineer, on a legacy conversion for Odyssey Logistics. Delivery throughput rose by roughly a third, and Odyssey recorded a 37 percent net cost saving against the conventional approach. Cognizant also narrowed its full-year constant currency growth guidance to 4.0% to 4.4%, from 4% to 5.5% earlier.

Those are the facts as reported. Everything below is my opinion.

My position: AI is writing more of the code, but it is not shrinking the need for engineers. It is changing what a good team looks like. The winners will run small, senior teams that own the result and treat AI output as a first draft, not a finished product.

Half the code, more people

The usual story says that when AI writes half the code, you need half the coders. Cognizant's numbers do not fit that story. More than half its code is AI-assisted, revenue per employee is improving, and it still has 10,100 more people than a year ago.

That tells me the work did not disappear. It moved. Less time goes into typing boilerplate, and more goes into deciding what to build, checking what the machine produced and making it work inside a messy client system.

The bottleneck moved to review

AI-assisted code is fast to write and easy to get wrong. Someone has to read it, test it, catch the security gap and say no when it solves the wrong problem. That someone is almost always an experienced engineer.

So the scarce skill is no longer output. It is judgment. A junior developer with an AI assistant can produce a lot of code. A senior developer with the same assistant can produce a lot of code that actually ships and does not break in production.

What buyers should ask their vendors

If you buy software delivery, the Odyssey example is the one to study. Seven people, a hard legacy conversion, a third more throughput and a 37 percent net saving. The point is not the tool. The point is a small team that knew what done looked like.

Ask how big the team really needs to be. A smaller senior team with good tooling can beat a large pyramid.

Ask who reviews the AI output. If the answer is vague, the risk is yours.

Ask what result you are paying for. Headcount on an invoice is not the same as working software.

A fair counterpoint

To be fair, AI is not only adding jobs at Cognizant. Its Project Leap program expects $150 million to $200 million in employee severance and other personnel costs, and third quarter bookings declined 7% year over year. The company also plans to hire 1,500 U.S. college graduates, which suggests it still sees a real role for junior talent. Headcount growth is not the whole story. My view is only that AI is reshaping teams faster than it is shrinking them.

The payoff

Cognizant shows that AI can assist on more than half the code while the company still adds people. The lesson for services leaders is that the value moved from writing code to judging it. Through AI Rescue & Technology Consulting, TDZ Pro provides developers, DevOps, QA, and PMs vetted over years of delivery, on a top-1% talent bench, and I took a firm from $6M to $60M in under three years. Small senior teams with clear ownership were the engine. Strong people on profitable work raise the whole company.

Want a small senior team that ships with AI and owns the result? Visit tdzpro.com.

From $6M to $60M: 7 Lessons from Scaling a Software Consulting Firm

Ashkan Rajaee — Sun, 01 Nov 2026 14:52:14 +0000

As a partner, I helped grow a software consulting company from about $6M to $60M in under three years. People usually ask me for the one trick behind that growth. There was no single trick. There were a handful of decisions, made early and repeated often, that kept the firm from breaking while it got bigger.

Later I founded and scaled a fully remote consultancy, and most of the same lessons held up. Here are the seven I come back to most.

1. Pick a Niche Before the Market Picks One for You

Early on, it is tempting to say yes to every project that pays. That feels like growth. In practice it spreads your team across too many stacks, industries and buyer types, and nobody gets good at anything.

The firms that scale fastest can finish this sentence clearly: "We are the team you call when you need X." When the answer is sharp, referrals get easier, proposals get shorter and hiring gets more focused. A clear niche is not a limit on growth. It is what makes growth repeatable.

2. Price for the Outcome, Not the Hour

Hourly pricing invites the buyer to compare you with the cheapest bid on the table. That is a race you do not want to win.

When we framed proposals around the business result the client needed, and the risk we were taking off their plate, the conversation changed. Buyers stopped asking why our rate was higher and started asking how fast we could start. The cheapest bid rarely wins the work that matters, and it almost never wins the renewal.

3. Treat Delivery Capacity as a Sales Constraint

The fastest way to damage a consulting brand is to sell work you cannot staff well. Every deal closed without the right people behind it becomes a delivery problem, then a reputation problem, then a pipeline problem.

So sales and delivery have to look at the same numbers. Before a big push, I wanted to know who would actually do the work, when they would be free and what we would need to hire. Growth that delivery cannot absorb is not growth. It is debt.

4. Hire Managers Before You Need Them

When a firm grows tenfold, the bottleneck is rarely demand. It is leadership capacity. By the time the founders feel overwhelmed, they are already months behind on hiring the people who should be running teams.

Bringing in delivery leads and account owners early felt expensive at the time. It was the reason we could keep saying yes without quality slipping. If you wait until the pain is obvious, you will be training new managers in the middle of a crisis.

5. Write the Playbook Once, Then Improve It Forever

Every time someone solved a recurring problem, from onboarding a new client to handling a missed deadline, we tried to write it down. Not a giant manual. A short, living document that the next person could follow.

That habit matters even more in a remote company. When people work across time zones, the written playbook is how culture travels. It also makes it possible to hire faster without everyone learning the same lessons the hard way.

6. Protect the Reputation Over Any Single Deal

In services, your reputation is the product. Some of the best decisions we made were deals we turned down: the project that did not fit our strengths, the client whose expectations we could not meet, the timeline that would have burned out the team.

Saying no is uncomfortable when you are trying to grow. But one bad engagement can cost more in referrals than it ever earns in revenue. The firms that last are the ones clients trust to tell them the truth.

7. Build Referral Loops, Not Just Pipelines

Outbound and marketing matter. Still, much of the most valuable work came from people who had already worked with us, or from someone they told.

That does not happen by accident. It comes from delivering well, staying in touch after a project ends and making it easy for happy clients to introduce you. A referral engine is slower to build than a cold outreach campaign, and it compounds for years.

What Ties the Seven Together

Look closely and these are not really separate lessons. They are one idea: grow only as fast as you can deliver with quality, and make every decision easier to repeat.

Niche, pricing, capacity, managers, playbooks, reputation and referrals all serve that idea. Get them roughly right and the revenue tends to follow. Get them wrong and growth becomes the thing that breaks you.

I took a firm from $6M to $60M in under three years.

If you are scaling a services business and want a partner who has been through it, visit https://tdzpro.com.

Barclays and Amex Are Cutting 5% for AI. Cut the Work First, Then the Jobs.

Ashkan Rajaee — Sat, 31 Oct 2026 13:25:36 +0000

On October 22, Barclays announced it will cut about 5% of its workforce, close to 5,000 jobs, mostly in support functions, as it moves more operations to AI systems. The next morning, American Express said it will eliminate 5% of its global workforce. Based on roughly 76,800 employees at the end of 2025, that is about 3,840 roles. CEO Stephen Squeri said the company needs "to become a more agile and efficient organization." Reuters counts Barclays among a long list of companies linking layoffs to AI this year, from HSBC to Kroger.

Those are the facts as reported. Everything below is my opinion.

My position: cutting headcount in the name of AI before the AI is doing the work is backwards. Redesign the work, prove the tools carry it, redeploy the people who know the process, and only then decide what roles you no longer need.

A round number is a budget, not a plan

Five percent is a clean figure for an earnings call. It is rarely what the work actually requires. When a cut is sized from the top down, the people who leave are often the ones who understand the exceptions, the workarounds and the customers who do not fit the standard flow. Those are exactly the cases AI handles worst.

If the automation is not ready, the remaining team absorbs the gap, service quality slips and the savings show up on paper long before they show up in operations.

Where AI really changes the workforce

In my experience, AI rarely removes a whole job on day one. It removes tasks: drafting, summarizing, first-pass review, routine tickets. That frees time, and the smart move is to decide in advance what that time is for.

Some of it should go to work that was always understaffed, like quality, security and customer follow-up. Some of it should become real savings. The order matters.

What leaders can take from this

Map the work before you map the cuts. List the tasks AI will take over and test it on live volume.

Keep the process experts. Move them into the roles that supervise, correct and improve the AI. They are your quality control.

Measure the outcome, not the headcount. Track error rates, cycle times and customer satisfaction before and after. If those slip, the cut was premature.

A fair counterpoint

To be fair, large banks and card issuers carry heavy support costs, and both companies may have tested these tools for months before announcing anything. Some roles really will disappear, and saying so early can be more honest than a slow drip of cuts. My view is only that the announcement should follow the proof, not lead it.

The payoff

The companies that get the most from AI will be the ones that treat it as a redesign of work, not a headcount target. Through AI Rescue & Technology Consulting, TDZ Pro provides developers, DevOps, QA, and PMs vetted over years of delivery, on a top-1% talent bench, and I took a firm from $6M to $60M in under three years. Getting the work right first was the engine. Strong people on profitable work raise the whole company.

Want help putting AI to work without breaking delivery? Visit tdzpro.com.

What Being Named One of Silicon Review's 30 Best CEOs Taught Me About Leading Remotely

Ashkan Rajaee — Fri, 30 Oct 2026 15:38:55 +0000

In January 2020, The Silicon Review named me one of its 30 Best CEOs of the Year. The recognition was for my work leading TopDevz, a software development consultancy built to deliver complicated projects for North American companies. I was proud of the mention. I was also clear-eyed about what it did not mean.

An award does not run a company. Cadence does. Trust does. Transparency does. The list was a snapshot. Leading a distributed team is a weekly practice. Years later, the habits that mattered then still matter at TDZ Pro and in every remote services team I advise. This piece is about those habits, not the trophy.

Recognition Is a Mirror, Not a Map

Being named among Silicon Review's 30 Best CEOs of the Year 2020 was useful in one practical way. It forced me to write down what I actually believed about leadership, instead of what sounded good in a profile.

The story people wanted was growth and awards. The story that kept people was quieter: how a remote company decides, how it shares bad news and how it keeps customers from feeling the distance between time zones. If the recognition taught me anything, it is that outside praise arrives after inside systems already work. Chase the systems. Let the lists catch up if they want to.

Trust Is the Operating System of a Remote Company

In an office, trust can hide behind proximity. People assume you are working because they see you at a desk. Remote strips that illusion away. That is a gift if you use it well.

I learned to treat trust as something you design, not something you declare in an all-hands. Design looks like clear outcomes, named owners and a shared definition of done. It looks like hiring people who can create clarity, then giving them authority that matches the responsibility. It does not look like "we hired adults, so leave them alone" with no feedback loop.

When trust is real, managers stop micromanaging calendars and start managing results. When trust is fake, Slack becomes a surveillance channel and everyone gets worse at telling the truth.

Cadence Beats Heroics

Distributed teams do not fail from a lack of talent nearly as often as they fail from a lack of rhythm. The companies that stay healthy have a boring, reliable beat:

A written weekly plan with one owner per outcome.
Short updates in a shared channel so status does not require a meeting.
Documented decisions, including the why, where a new hire can find them.
Overlap windows across time zones treated as scarce, not optional.
One-on-ones about blockers and growth, not status theater.
A playbook that grows whenever the same question is asked three times.

None of that is glamorous. Together it is how you scale past the bandwidth of a few human routers. Heroic late nights may save a sprint. Cadence saves the company.

I later took those same habits into building and leading remote services work at scale. As a partner I had already helped grow a consulting firm from about $6M to $60M. The award did not create that operating discipline. The discipline made the award make sense in hindsight.

Transparency Is How Distance Stops Feeling Like Distance

Remote customers and remote teammates share a fear: that they are the last to know. Transparency closes that gap.

For teams, that means putting priorities, risks and tradeoffs in writing early. It means celebrating the person who escalates a problem on Tuesday, not only the person who quietly fires a drill on Friday. For customers, it means honest status, clear owners and no surprise about capacity.

I would rather send an uncomfortable update early than a polished apology late. Distributed companies that hide bad news do not stay distributed for long. They stay reactive.

What the Award Did Not Change

The Silicon Review list did not change how I hire, how I price or how I run a week. Those were already the work. What it did change was my willingness to talk about the unsexy parts in public.

Leaders get rewarded for narrative. Companies get rewarded for habits. If you only optimize for the first, you get a nice quote and a fragile org chart. If you optimize for the second, you can survive a bad quarter, a lost deal or a key person going on leave without the whole system wobbling.

That distinction still guides me. When I look at a remote team now, I ask:

Can a new hire learn how work gets done without pinging the same three veterans?
Are outcomes owned by names, or by a group channel?
Do people know what good looks like without watching someone perform it?
Is writing valued enough that meetings actually shrink?
When something breaks, does the truth surface early?

If those answers are weak, no award, tool or brand refresh will fix the culture.

Habits Over Headlines

Leading remotely well is not about proving you do not need an office. It is about building trust people can feel, a cadence people can plan around and transparency people can rely on when things go wrong.

The Silicon Review recognition was a kind milestone for TopDevz and for me personally. The lasting lesson was simpler. Be the kind of leader whose company still works on the weeks nobody is writing about you.

I took a firm from $6M to $60M in under three years.

If you are building or scaling a remote services team and want to compare notes on trust, cadence and transparency, you can find me at https://tdzpro.com.

Ashkan Rajaee is the founder of TDZ Pro. As a partner, he helped grow a software consulting company from about $6M to $60M in under three years, and he founded and scaled a fully remote software consultancy. In 2020, The Silicon Review named him one of its 30 Best CEOs of the Year for his leadership at TopDevz.

Infosys Grew AI Revenue 29% in a Quarter. Its Clients Want the Savings Back.

Ashkan Rajaee — Fri, 30 Oct 2026 13:55:52 +0000

Infosys reported its Q2 FY27 results on October 23. AI revenue reached 10.5% of total revenue, up from 8.2% the quarter before, and grew 29% sequentially. Total revenue grew 1.5% year over year in constant currency. The company lowered its full-year growth guidance to 1% to 2%, from 1.5% to 3% earlier. CFO Jayesh Sanghrajka said Infosys has seen "pricing pressure on the back of competitive intensity and higher ask on productivity," and expects that pressure to continue into the second half of the year.

Those are the facts as reported. Everything below is my opinion.

My position: clients have figured out that AI makes delivery cheaper, and they want their share of the savings. Selling hours is getting harder every quarter. The firms that win will price the outcome and staff it with senior people who know how to use the tools.

The productivity dividend belongs to someone

When a team ships the same work in fewer hours, somebody keeps the difference. For years, services firms kept it by billing the same rate card and quietly improving margins. Buyers have caught up. They read the same headlines about AI coding assistants and test automation, and they now walk into renewals expecting a lower number.

That is what "higher ask on productivity" means in plain words. The client is saying: you got faster, so I should pay less.

Why hourly billing is the weak spot

If you sell time, every efficiency gain is a revenue cut. You can fight that by hiding the gains, but buyers are not naive, and the trust cost is high. The alternative is to stop selling time.

Fixed-scope projects, outcome-based milestones and managed capacity with clear deliverables all let a vendor keep part of the productivity gain while the client still pays less than before. Both sides win, and nobody has to pretend AI did not happen.

What smaller firms can take from this

Large IT services companies are built on headcount, so this shift hurts them most. Smaller firms have an advantage if they move first.

Price the result. Agree on what done looks like and what it is worth to the client, then price against that.

Staff senior. One experienced engineer with good AI tooling often replaces a pyramid of junior billable hours. Clients notice the difference in quality and speed.

Show the math. Tell the client where AI saved time and what you did with it. Transparency turns a pricing fight into a partnership conversation.

A fair counterpoint

To be fair, Infosys also signed $5.2 billion in large deals this quarter, including a net-new mega deal of over $2 billion, so demand for big transformation work is real. Pricing pressure is not the same as shrinking demand. My view is only that the old way of charging for that demand is under strain.

The payoff

Infosys shows that AI revenue and pricing pressure can grow at the same time. The lesson for services leaders is to stop selling effort and start selling outcomes. Through AI Rescue & Technology Consulting, TDZ Pro provides developers, DevOps, QA, and PMs vetted over years of delivery, on a top-1% talent bench, and I took a firm from $6M to $60M in under three years. Clear scope and senior people were the engine. Strong people on profitable work raise the whole company.

Want help delivering outcomes instead of hours? Visit tdzpro.com.

What 100+ RemotePreneurs Interviews Taught Me About Building Remote-First Companies

Ashkan Rajaee — Thu, 29 Oct 2026 15:42:39 +0000

For a stretch of years I hosted RemotePreneurs, a YouTube interview series with founders and operators building companies without a traditional office as the center of gravity. After more than a hundred conversations, the patterns stopped being anecdotes and started looking like an operating system.

This is not a highlight reel of famous guests. It is what kept showing up when people who actually run remote-first companies talked about what works, what breaks and what they would do earlier next time.

I later founded and scaled a fully remote software consultancy myself, and as a partner I had already helped grow a consulting firm from about $6M to $60M. The interviews did not replace that experience. They sharpened it. Below are the lessons I still use.

Remote-First Is a Design Choice, Not a Perk

The strongest guests did not treat remote as "office culture over Zoom." They designed the company as if co-location were the exception.

That sounds obvious. In practice it means writing down how decisions get made, how work is handed off and how performance is judged, instead of hoping people absorb it by sitting near the right hallway. Guests who skipped that design phase often described the same failure: a few people became human routers for every question, and growth stalled at the bandwidth of those people.

Remote-first is not the absence of an office. It is the presence of an operating system that works when nobody shares a room.

Trust Is Built With Cadence, Not Slogans

Almost every durable remote company had a rhythm: weekly priorities, clear owners, visible progress and a small number of meetings that existed for decisions rather than status theater.

Trust was not "we hired adults, so leave them alone." Trust was "we made expectations legible, so people can succeed without guessing." The interviews that stuck with me were rarely about ping-pong tables or home-office stipends. They were about how a team knows what good looks like on Friday when nobody watched them on Tuesday.

Async Is a Skill, Not a Default Setting

Many guests said they were "async first," then admitted their Slack was still a second job. The ones who made async work treated writing as a core competency.

They wrote proposals before meetings. They recorded short updates instead of booking thirty minutes for a monologue. They accepted that a thoughtful reply tomorrow beats a half-baked reply in two minutes. And they protected overlap hours for the few conversations that truly need back-and-forth: conflict, ambiguity, and relationship repair.

Async fails when it is used to avoid hard talks. It works when it is used to prepare for them.

Hire for Ownership, Then Give People Something Real to Own

Remote companies that scaled well hired people who could create clarity, not just consume it. Job descriptions sounded less like task lists and more like outcomes.

Several founders described the same early mistake: hiring for skills they could supervise closely, then wondering why remote felt harder than an office. Supervision does not travel well across time zones. Ownership does. The follow-on lesson was just as important: ownership without authority is theater. If you want someone to own a result, give them the decision rights that match it.

Culture Is What You Tolerate in Writing

In an office, culture leaks through tone of voice and who gets interrupted. Remote, culture shows up in docs, pull requests, issue threads and how leaders respond when something goes wrong.

Guests who were honest about culture talked less about values posters and more about examples: what happened the last time a deadline slipped, a customer was upset or a hire was wrong. Remote teams copy what leaders do in public channels. If leaders only praise speed, people hide quality problems. If leaders reward clear updates and early escalation, people tell the truth sooner.

Daily Rituals That Kept Showing Up

Across very different industries, a handful of practices repeated:

A written weekly plan with a single owner per outcome.
A short daily or near-daily update in a shared channel (not a meeting).
Documented decisions, including the "why," in a place new hires can find.
Deliberate overlap windows across time zones, treated as scarce and valuable.
Regular one-on-ones focused on blockers and growth, not status regurgitation.
A playbook that grows whenever the same question is asked three times.

None of these are glamorous. Together they are how remote companies avoid becoming a pile of private chats and forgotten promises.

What Remote Does Not Fix

Remote work does not fix a fuzzy strategy, a weak manager or a product nobody wants. Several interviews were cautionary for that reason. Founders who went remote to escape hard management problems usually recreated those problems in a chat app.

Remote also does not mean zero in-person time for every company. Some guests used occasional on-sites for planning or bonding. The point was never purity. The point was that the default system still worked on the fifty-one weeks nobody flew anywhere.

How I Use This Now

When I look at a remote team, I ask a short set of questions I stole from those conversations:

Can a new hire find how work gets done without asking the same three veterans?
Are outcomes owned by names, or by group chat?
Do people know what "good" looks like without watching someone do it?
Is writing valued enough that meetings shrink?
When something breaks, does the truth surface early?

If the answers are weak, no tool migration will save the culture.

The Short Version

After 100+ RemotePreneurs interviews, my conviction is simple. Remote-first companies win when they design for clarity: written expectations, real ownership, async skill, a steady cadence and leaders who model the behavior they want copied. The office was never the real operating system. The habits were.

I took a firm from $6M to $60M in under three years.

If you are building or scaling a remote services team and want to compare notes, you can find me at https://tdzpro.com.

AI Won't Replace B2B Sellers, But Sellers Using AI Will Replace Those Who Don't

Ashkan Rajaee — Thu, 29 Oct 2026 13:32:54 +0000

AI will not replace strong B2B sellers. That sentence is true, and it is also incomplete. The sellers who treat AI as a research assistant, a prep coach and a writing partner are already outperforming the ones who treat it as a threat or a gimmick.

I have spent years selling and leading sales for technical services. As a partner, I helped grow a software consulting company from about $6M to $60M in under three years. Later I founded and scaled a fully remote consultancy. Across both, the pattern was the same: tools change who gets to the meeting prepared. They do not change who earns trust once the meeting starts.

This piece is about where AI actually helps in B2B sales, where humans still win, and how to build a habit that compounds.

The Fear Is Pointed at the Wrong Thing

Most of the panic about AI in sales assumes the job is sending more messages. If that were the whole job, yes, machines would crush people on volume. But complex B2B work is not a volume game. It is a judgment game.

Enterprise buyers are not choosing the vendor who emailed them first. They are choosing the partner they believe will understand the problem, tell them the truth and deliver. AI can help you look sharper before that conversation. It cannot sit in the room and own the outcome.

The sellers at risk are not the ones who refuse to become robots. They are the ones who refuse to get better prep, clearer writing and faster research while their competitors do.

Where AI Helps (And Should Be Used Every Week)

There are a few places AI is already a clear advantage for a human seller.

Research before the call. Pulling recent news, earnings language, org charts, tech stack clues and likely pain points used to take an hour. A good prompt and a careful read can cut that to minutes. The skill is not dumping a summary into a deck. The skill is deciding which three facts matter for this buyer.

Personalization that is specific, not creepy. AI is useful for a first draft of outreach that references something real: a product launch, a hiring spike, a regulatory change. The seller still has to cut anything that sounds generic or invasive. Specificity without judgment is just noise with a name on it.

Call prep and objection maps. Before a discovery call, I like a short brief: who is in the room, what each person might care about, three questions worth asking and the objections that usually show up for this kind of deal. AI is excellent at drafting that brief. The seller is responsible for editing it against what they know of the account.

Follow-up writing. After a call, a clean summary, next steps and a proposal outline should go out the same day. AI can turn rough notes into a readable first draft. The seller owns accuracy, tone and the promise being made.

None of this replaces selling. It removes the busywork that used to eat the hours when thinking should happen.

Where Humans Still Win

If AI handles prep, what is left for people? The parts that decide the deal.

Discovery that listens. Buyers can tell when you are running a script. They can also tell when you are following a thread they just opened. That requires presence, not a model.

Trust under pressure. When a stakeholder pushes back on price, timeline or risk, the answer is rarely a paragraph from a tool. It is judgment: when to hold the line, when to reframe and when to walk away.

Multi-threaded deals. Complex services sales have champions, blockers, procurement and quiet influencers. Mapping that and keeping everyone aligned is still human work.

Knowing when not to sell. The best sellers I know protect the firm's reputation. They will say a deal is not a fit. AI optimized for activity will almost never choose that path.

A Simple Weekly Operating Rhythm

You do not need a stack of ten tools. You need a rhythm.

Before every meaningful call, spend ten minutes with AI on research and a one-page brief. Edit it yourself.
After every call, draft the follow-up with AI from your notes, then rewrite the promises in your own words.
Once a week, feed your lost-deal notes into a prompt and ask for patterns in objections. Keep a living list of how you answer the top five.
Never send the first draft. Always cut fluff, check facts and make sure the CTA matches what you can actually deliver.

That last point matters in services. AI will happily help you overpromise. Delivery still has to be real.

How This Differs From "Replace the SDR"

There is a separate conversation happening about AI SDR agents that book meetings at a fraction of a human salary. Some of that math is real for top-of-funnel volume. It is not the same as winning a technical services deal.

In services, the buyer is hiring people. An automated sequence can open a door. A prepared human walks through it. The winning model is hybrid: AI for speed and coverage, humans for trust, objections and the close.

If your team is chasing pure automation as a cost cut, ask a harder question: are you optimizing for meetings booked, or for revenue that renews and refers?

What I Tell Sellers on My Teams

I do not ask people to become prompt engineers. I ask them to become relentlessly prepared.

Show up knowing the account. Write like a human. Use tools to compress the work that used to justify being underprepared. Measure yourself on quality of conversations and clarity of next steps, not on how many sequences you launched.

The sellers who do that will not be replaced by AI. They will replace the sellers who do not.

The Short Version

AI is a force multiplier for B2B sellers who already understand the craft. Use it for research, personalization, call prep and follow-up. Keep humans on discovery, trust, stakeholder management and the decision to walk away. Build a weekly habit, not a tool graveyard.

I took a firm from $6M to $60M in under three years.

If you want help building a sales team that uses AI the right way for technical services, visit https://tdzpro.com.

Zoho Froze Raises to Avoid Layoffs. AI Is Not Free, and Leaders Should Budget for It.

Ashkan Rajaee — Wed, 28 Oct 2026 15:38:58 +0000

On October 13, Zoho co-founder and chief scientist Sridhar Vembu said on X that the company will not give its usual annual pay increase this year. He said server prices have increased fourfold, AI usage is raising expenses quickly, and the outlook for software is uncertain. Zoho has also cut its marketing budget, and Vembu said the company has not grown its employee count in 18 months. He wrote, "I have apologised for not being able to avoid this."

On October 15, CEO Mani Vembu said the company chose to skip raises rather than lay people off or raise prices, because the business is still growing and it has over a million customers to support.

Those are the facts as reported. Everything below is my opinion.

My position: whatever you think of the decision, Zoho is saying out loud something many companies are not. AI has a cost, and someone pays it.

The hidden bill

Most of the AI conversation is about savings. Do more with fewer people, ship faster, cut hours. Zoho is describing the other side: the compute, the servers and the usage that make those savings possible are expensive and rising.

If a company that runs its own data centers feels that pressure, smaller businesses buying AI tools by usage will feel it too.

Raises or layoffs

Mani Vembu said layoffs are common but did not feel right while the business is still growing. Spreading the cost across everyone, instead of removing some people, is a defensible choice. It is also a hard one. Employees lose real purchasing power, and some will leave.

The public reaction was sharp, and I understand why. A pay freeze is painful even when it is honestly explained.

What leaders can take from it

Put AI spend in the budget as its own line, with an owner, and review it every month.

Measure the return. If a tool saves ten hours a week and costs more than those hours are worth, that is not a win.

Decide in advance who carries the cost if it rises: customers, shareholders or employees. Do not let it get decided by accident.

A fair counterpoint

To be fair, the critics have a point too. Asking employees to absorb costs while the company says it is still growing is a tough message, and a pay freeze compounds with inflation. Mani Vembu acknowledged there is no single right answer and said every software business will be having this discussion. I agree with that. My view is only that being open about the tradeoff is better than hiding it.

The payoff

Zoho's choice will be judged over the next few years, and the company itself said this period will be decisive. The lesson for everyone else is simpler: count the cost of AI as carefully as the benefit. Through AI Rescue & Technology Consulting, TDZ Pro provides developers, DevOps, QA, and PMs vetted over years of delivery, on a top-1% talent bench, and I took a firm from $6M to $60M in under three years. Hiring well and watching costs honestly was the engine. Strong people on a clear budget raise the whole team.

Want help building a team and a budget that hold up? Visit tdzpro.com.

Hire Managers Before You Need Them: What Scaling 10x Taught Me

Ashkan Rajaee — Wed, 28 Oct 2026 14:36:09 +0000

When people ask me what I learned from helping a software consulting company grow from about six million dollars to sixty million in under three years, they usually expect an answer about sales. Sales mattered, of course. But the lesson that has stayed with me longest is about people, and specifically about managers. The single biggest constraint on our growth was not demand. It was leadership capacity. And the fix was to hire and develop managers before we felt we needed them.

I carried that lesson into building a fully remote consultancy of my own, and it has proven true again and again. Here is what I learned.

Growth Breaks the Org Chart First

In the early days of a services firm, the founders or partners do almost everything. They sell, they scope, they staff, they solve problems for clients and they mentor the team. That works until it does not.

The breaking point arrives quietly. Response times slip. Senior people spend their days in status meetings. A client escalation lands on your desk that someone else should have caught a week ago. New hires feel lost because nobody has time to onboard them properly. Each of these feels like a small problem, but together they signal that the organization has outgrown its leadership structure.

By the time you clearly see the problem, you are already behind. Hiring a good manager takes time. Getting that manager up to speed takes more time. If you wait until the pain is obvious, you will spend months operating in a degraded state, and growth will stall precisely when the market is giving you an opportunity.

The Math of Management Capacity

A useful way to think about this is capacity planning for leadership. Every manager can effectively support a limited number of people and a limited number of client relationships. That number depends on the complexity of the work, the experience of the team and the maturity of your processes, but it is always finite.

When you forecast growth, most companies forecast revenue and headcount. Fewer forecast management capacity. Yet if you plan to double your delivery team in a year, you will need roughly double the leadership bandwidth to support it. If you do not plan for that, the existing managers absorb the load until they burn out or quality drops.

I started treating management capacity as a leading indicator. If we expected to add a certain number of people over the next two quarters, we needed to have the managers to support them in place, or at least in the pipeline, before the new hires arrived.

Why Hiring Ahead Feels Wrong

Hiring managers ahead of need feels uncomfortable for good reasons. Managers are expensive. In a services business, they may not be fully billable. When cash is tight, adding overhead before revenue arrives looks like a risk.

But I came to see the opposite risk as larger. Without enough managers, you cannot onboard people well, you cannot keep quality consistent and you cannot give clients the attention that earns renewals and referrals. Under-managed growth is fragile growth. Every new client becomes a potential fire, and fires consume far more senior time than prevention would have.

The trick is to make the investment deliberately. You do not need to build a full management layer years in advance. You need to stay one step ahead, with a clear view of when the next leadership role will be required and a plan to fill it in time.

Promote, Hire or Both

There are two sources of managers: people you grow internally and people you bring in from outside. I believe you need both.

Internal promotions are powerful. The people you promote already understand your culture, your clients and your standards. Promoting from within also shows the team that there is a path forward, which helps retention. But promotion is not a reward for being a strong individual contributor. The skills are different. A brilliant engineer may not enjoy or excel at coaching, planning and handling difficult conversations. I learned to ask whether someone wanted to lead and whether they had already been leading informally before making that move.

External hires bring something different: experience at a larger scale. When you are about to grow into a size you have never operated at, it helps to have people who have already seen what that looks like. They bring patterns, processes and judgment that would take years to develop internally.

The best results came from mixing the two. Experienced external leaders helped shape the systems, and internally promoted managers kept the culture strong.

Develop Managers Deliberately

Hiring or promoting a manager is the beginning, not the end. New managers need support, especially in a fast-growing firm where the expectations keep changing.

A few practices made a real difference for me.

Define the role clearly. What decisions does this manager own? What do they escalate? How is success measured? Ambiguity at the management level spreads quickly to the whole team.

Give them a real onboarding. Managers need context on clients, financials, people and priorities. Throwing a new manager into the deep end and hoping they swim wastes their potential.

Create regular forums for managers to learn from each other. Peer learning among managers is one of the fastest ways to spread good practices and catch problems early.

Coach them on the hard parts. Most new managers struggle with the same things: giving direct feedback, delegating instead of doing, and saying no to clients or leadership. Talking about these openly helps.

Remote Makes This More Important

In a fully remote company, managers carry even more weight. There is no hallway, no lunch table and no chance to notice that someone looks stressed. Communication has to be intentional, and managers are the ones who make it intentional.

Remote managers need to be strong writers, consistent communicators and good at building trust without physical presence. They need to run effective one-on-ones, notice when engagement drops and create clarity across time zones. When I built a remote consultancy, I paid particular attention to these skills during hiring, because a remote manager who struggles with communication can leave an entire team adrift without anyone realizing it for weeks.

Signals That You Are Already Late

If you are wondering whether you need more managers now, here are some signs I learned to watch for.

Founders or senior partners are involved in day-to-day delivery decisions on most projects.

Onboarding new people takes longer and feels less consistent than it used to.

Client issues surface late, often only when the client complains.

Your best people are working long hours and have stopped proposing improvements.

One-on-ones are getting cancelled or skipped because there is no time.

If several of these sound familiar, you are not just growing. You are straining. The time to hire was probably a quarter ago, which means the next best time is now.

Leadership Is the Product

In professional services, the quality of your leadership is ultimately the quality of your product. Clients may hire you for technical skill, but they stay because of how the work is managed: the clarity, the reliability, the way problems are handled. Managers are the people who deliver that experience at scale.

Scaling tenfold taught me that growth is not just about winning more work. It is about building the capacity to deliver that work well, again and again, as the company gets bigger. Hiring managers before you need them is one of the highest leverage decisions a growing firm can make. It feels expensive in the moment. In hindsight, it is almost always the reason growth held together.

I took a firm from $6M to $60M in under three years.

If you are planning your next stage of growth and want to build the leadership capacity to support it, visit https://tdzpro.com.
Ashkan

AI SDRs Cost $1 a Lead or $3,750 a Month. Humans Still Close the Deal.

Ashkan Rajaee — Tue, 27 Oct 2026 15:44:07 +0000

A September 2026 comparison of 13 AI sales development tools at aiagentforsales.com lists published prices from $1 per qualified lead (HubSpot Breeze Prospecting) to $3,750 a month and up for an autonomous AI BDR (11x Alice Growth). It compares those numbers with $98,000 to $173,000 a year for a fully loaded human SDR. The same page cites 2026 industry surveys: 22% of teams say they fully replaced human SDRs with AI, 45% run hybrid models, and about 2% report pure AI SDR deployments that stuck.

Those are the figures as reported. Everything below is my opinion.

My position: AI SDRs are very good at the top of the funnel and weak where B2B deals are actually won. The winning model is hybrid. AI does the research and the first touch. Humans own trust, objections and the close.

The price gap is real

On paper, the math is obvious. A tool that costs a few hundred or a few thousand dollars a month against a six-figure salary looks like an easy decision. For list building, enrichment and first drafts of outreach, the tools are fast and cheap.

The results gap is real too

That 2% figure matters more than the price. If almost no one is succeeding with pure AI outbound, the savings are not the whole story. Volume without judgment fills inboxes, burns domains and trains buyers to ignore you.

In B2B services, the buyer is choosing people they will trust with a project. An automated sequence can start that conversation. It cannot carry it.

Where AI helps and where humans win

AI helps with research before a call, personalizing the first message, sorting replies and keeping follow-ups on time.

Humans win on discovery, handling objections, managing several stakeholders and knowing when not to push.

The best setup I have seen lets AI make every salesperson better prepared, not lets AI replace them.

A fair counterpoint

To be fair, some teams selling simple, low-cost products may get more out of full automation than a services firm will. And the tools improve every quarter. My view applies to complex, relationship-driven sales, where a wrong message costs more than a slow one.

The payoff

AI will not replace B2B sellers. Sellers who use AI well will outperform those who do not. Through AI Rescue & Technology Consulting, TDZ Pro provides developers, DevOps, QA, and PMs vetted over years of delivery, on a top-1% talent bench, and I took a firm from $6M to $60M in under three years. People who earned trust were the engine. Strong sellers with good tools raise the whole pipeline.

Want help building a sales team that uses AI the right way? Visit tdzpro.com.

Kroger Is Cutting 3,000 Corporate Jobs. The Real Target Is Layers, Not Just AI.

Ashkan Rajaee — Tue, 27 Oct 2026 13:38:35 +0000

On October 12, Kroger told employees it plans to eliminate about 3,000 corporate roles over the next three years. Bloomberg reported that is roughly 37% of about 8,200 corporate employees, and one of the largest cuts in the company's 143-year history. The grocer cut nearly 1,000 corporate jobs last year.

In a memo, CEO Greg Foran wrote that Kroger has "more layers, more handoffs and more overhead than we need." He also wrote that the company must "take advantage of technology" and reduce duplicative work. Kroger has not said which departments or roles are affected and expects to share details in the coming months.

Those are the facts as reported. Everything below is my opinion.

My position: the headlines frame this as an AI story, but the memo reads like an organization story. Layers and handoffs are management choices, and technology only makes it easier to finally act on them.

Why I read it this way

Look at the language. Layers. Handoffs. Overhead. None of those words describe a machine replacing a person. They describe a company that built too many steps between a decision and a result.

Technology matters here, because it can remove some of those steps. But a tool cannot decide that a level of management is unnecessary. People decide that.

The risk of calling it AI

When a layoff is explained mainly by AI, two things happen. Employees assume the tools are coming for their jobs, and trust drops. And leaders skip the harder question of whether the structure was ever right.

If Kroger ends up with the same slow decisions and fewer people, the cuts will not have worked, whatever tools it buys.

What other leaders can take from it

Map the handoffs before you cut anything. Count how many steps a decision takes and who touches it.

Be honest about the reason. If the goal is a flatter company, say so. If AI really replaces a task, say which one.

Invest in the people who stay. A leaner team needs better tools and clearer ownership, not just more work.

A fair counterpoint

To be fair, Foran has a case. Grocery is a thin-margin business facing Walmart, Costco and Amazon, and he wrote that savings will go toward lower prices, the shopping experience and frontline associates. A company that simplifies can compete better, and three years gives it time to do this carefully. I just think the public explanation matters. Employees at every company are watching how these decisions get described.

The payoff

Kroger's cuts will play out over three years, and the details are still to come. The lesson for any company is to fix the structure first. Through AI Rescue & Technology Consulting, TDZ Pro provides developers, DevOps, QA, and PMs vetted over years of delivery, on a top-1% talent bench, and I took a firm from $6M to $60M in under three years. Hiring well and keeping teams lean and accountable was the engine. Strong people with clear ownership beat extra layers every time.

Want help building a lean, accountable engineering team? Visit tdzpro.com.

Building a Referral Engine in B2B Services

Ashkan Rajaee — Mon, 26 Oct 2026 15:42:15 +0000

Ask almost any leader of a professional services firm where their best clients come from, and you will hear some version of the same answer: referrals. Referred clients tend to trust you faster, negotiate less aggressively and stay longer. Yet most firms treat referrals as luck. They are grateful when one arrives and do little to make the next one more likely.

Over the years, both as a partner in a software consulting company that grew rapidly and as the founder of a fully remote consultancy, I learned that referrals can be engineered. Not manipulated, but deliberately cultivated. A referral engine is a set of habits and systems that make it easy and natural for satisfied people to send good business your way. Here is how I think about building one.

Referrals Start With Delivery

There is no shortcut around this point. People refer firms that made them look good. If your delivery is inconsistent, no referral program in the world will fix it. The foundation of every referral engine is work that clients are proud to talk about.

That means more than technical quality. It means communication that keeps clients informed, honesty when things go wrong and a sense that your team genuinely cares about the client's success. Clients remember how a partner behaved during a difficult moment far longer than they remember a smooth sprint. Handling problems well is often what turns a satisfied client into an enthusiastic advocate.

I encourage leaders to look at every engagement and ask a simple question: if this client were asked about us tomorrow, what would they say? If the honest answer is lukewarm, fix delivery before worrying about referrals.

Know Who Can Refer You

Most firms think only about clients as referral sources. Clients matter most, but they are not the only ones.

Former employees of your clients are a rich source. When a champion moves to a new company, they often bring trusted partners with them. Staying in touch with people as they change roles is one of the most reliable ways I have seen to generate new opportunities.

Complementary firms are another. Agencies, advisors and consultancies that serve the same buyers but do not compete with you often encounter needs they cannot meet. If they trust you, they will send those needs your way, and you can return the favor.

Your own team, past and present, can also refer you. People who had a good experience working with you become ambassadors wherever they go next.

Mapping these groups gives you a clearer picture of where referrals can come from and who deserves your attention.

Make It Easy to Refer You

Even people who love your work may struggle to refer you if they cannot explain what you do. A vague description like "they do software" does not help anyone make an introduction.

I learned to give advocates simple language. Who is the ideal client? What problem do you solve best? What does a good first conversation look like? When a referrer can describe you in one or two clear sentences, introductions happen far more often.

It also helps to make the next step obvious. If someone says, "You should talk to my friend," know exactly what you will do: a short introduction email they can forward, a brief call to understand the situation and a respectful approach that reflects well on the person who referred you.

Ask, but Ask Well

Many services leaders are uncomfortable asking for referrals. They worry it sounds needy or transactional. But clients who are happy with your work usually want to help. They simply do not think of it unless prompted.

The key is timing and framing. The best moment to ask is right after you have delivered something the client values: a successful launch, a resolved crisis, a milestone that made their team look good. In that moment, a simple question works: "Is there anyone else in your network facing a similar challenge who might benefit from a conversation?"

Be specific when you can. Asking whether they know a leader at a similar company who is wrestling with a particular problem is easier to answer than a generic request for names.

And never make the client feel obligated. A referral given reluctantly does more harm than good.

Close the Loop

One of the most overlooked parts of a referral engine is gratitude. When someone refers you, they are lending you their reputation. Treat that seriously.

Thank them promptly, whether or not the introduction turns into business. Keep them informed, within the bounds of confidentiality, about how things progressed. If the referral becomes a client, let the referrer know their trust was well placed.

People who feel appreciated refer again. People who never hear what happened often assume their introduction was ignored and quietly stop making them.

Build Relationships Before You Need Them

The strongest referral engines are built on relationships that existed long before anyone needed anything. That means staying in touch with past clients, sharing useful ideas, checking in when you see news about their company and being generous with your own introductions.

I made a habit of helping people in my network without expecting anything in return: introducing them to talent, connecting them with other experts, offering a perspective on a problem. Generosity compounds. Over time, people remember who helped them, and they look for ways to return the favor.

In a remote company, this takes more intention. There are fewer chance encounters, so you have to schedule the conversations that would otherwise happen naturally. A short, genuine check-in every few months keeps relationships warm without feeling forced.

Measure What Matters

A referral engine benefits from the same discipline as any other growth channel. Track where your opportunities come from. Know which clients and partners have referred you, how those deals progressed and which relationships deserve more investment.

You do not need complex software to start. A simple record of referral sources, introductions and outcomes will reveal patterns quickly. You may find that a few relationships account for a large share of your best work, which tells you exactly where to focus your attention.

Be careful not to let measurement turn relationships into transactions, though. The point of tracking is to be more thoughtful, not more mechanical.

Should You Pay for Referrals?

Some firms offer referral fees, and in certain partnerships that can make sense, especially with complementary firms that expect it as a normal business arrangement. If you do it, be transparent and make sure it does not create conflicts of interest for the people involved.

With clients, I have generally found that recognition and reciprocity matter more than money. Most clients refer you because they want their peers to succeed and because it reflects well on their own judgment. A thoughtful thank-you and a genuine effort to help them in return usually mean more than a fee.

The Compounding Effect

What makes a referral engine powerful is that it compounds. Each well served client becomes a potential source of the next client, who becomes a source of the one after that. Over time, a firm with a strong referral engine spends less on acquisition, closes deals faster and attracts clients who already trust it.

That compounding only works if you protect the foundation. Deliver work worth talking about, make it easy to talk about you, ask at the right moments, show gratitude and invest in relationships for the long term. Do those things consistently, and referrals stop being luck and start being one of the most dependable growth channels you have.

I took a firm from $6M to $60M in under three years.

If you want help designing a referral engine and sales system for your services business, I would be glad to compare notes. You can find me at TDZ Pro, https://tdzpro.com.