DEV Community: Rishita Sharma

A practical growth loop for early products

Rishita Sharma — Fri, 02 Oct 2026 07:15:15 +0000

Early growth gets clearer when treated as a learning loop, not a channel checklist.

Start with one painful use case and a narrow audience. Then run small experiments that produce real conversations: a useful guide, a focused landing page, a lightweight tool, or a hands-on onboarding session.

Track the signals that show learning: repeated customer language, activation, retention, and the objections that keep coming up. The best experiment is the one that improves the next message or product decision.

Once one path shows repeatability, document it before adding more channels. Sustainable growth usually comes from making one useful promise easier to discover, understand, and try.

How Small Feedback Loops Make Product Decisions Lighter

Rishita Sharma — Thu, 01 Oct 2026 16:02:00 +0000

Product work gets heavy when every decision depends on a large research project. A smaller feedback loop can keep the team moving without hiding uncertainty.

A useful weekly rhythm is simple:

Choose one uncertainty that matters.
Run the smallest test that can teach you something.
Compare what you expected with what you observed.
Record the decision and the next step.

The important part is the decision log. Keep it short, share it where the team already works, and revisit it during planning. The goal is not perfect prediction. It is making learning visible soon enough to change what happens next.

What is the smallest feedback loop that has improved a product decision for your team?

Hiring Engineers vs Outsourcing: A Practical Decision Framework

Rishita Sharma — Thu, 01 Oct 2026 15:15:49 +0000

For a young company, the question is rarely “Should we hire or outsource?” in the abstract. The better question is: which capability must become a permanent advantage, and which piece of work can be bought safely for a defined period?

That framing prevents two expensive mistakes: hiring a large team before the problem is understood, and outsourcing the exact knowledge the company will need to own later.

Start with the work, not the job title

Break the roadmap into three buckets:

Core learning: work that helps you understand users, workflows, or product-market fit.
Core advantage: technology or domain knowledge that will differentiate the business.
Commodity delivery: well-understood work with clear inputs and outputs.

Core learning usually needs close founder involvement. Core advantage should gradually be owned by an internal team. Commodity delivery can be outsourced when the quality bar and acceptance criteria are clear.

This is more useful than saying “we need three developers.” You may actually need one product-minded engineer to run experiments, a specialist for a short integration, and a reliable partner for a bounded piece of delivery.

When hiring is the better choice

Hire when the work is continuous, ambiguous, and tightly connected to customer feedback. An internal engineer is a better fit when they will:

make product trade-offs every week;
work directly with users or operations;
maintain systems after launch;
build context that compounds over time; or
protect sensitive domain knowledge.

A good first hire is not necessarily the most senior person available. It is someone who can make sensible decisions with incomplete information, communicate trade-offs, and leave the codebase easier to understand than they found it.

Before hiring, define the first 90-day outcome. “Build the platform” is not an outcome. “Enable ten target customers to complete the core workflow and give us reliable usage data” is much more useful.

When outsourcing is the better choice

Outsource when the work is bounded, specialized, or temporarily exceeds your capacity. Examples include a one-time design system, a security review, a migration, a narrowly scoped mobile build, or a well-specified integration.

Outsourcing works best when you can provide:

a written scope and explicit non-goals;
examples of acceptable quality;
one decision-maker on your side;
access to a staging environment and test data;
milestones tied to working software; and
a handover plan that includes documentation and credentials ownership.

Avoid outsourcing a vague idea and hoping a vendor will discover the product for you. You may receive polished output that solves the wrong problem.

The hybrid path is often healthiest

Many startups benefit from a small internal product owner plus a carefully scoped external team. The internal person owns priorities, user feedback, architecture decisions, and acceptance. The external team accelerates delivery without becoming the only source of context.

Set a weekly demo with real scenarios, not slide-deck status updates. Keep the repository, cloud account, domain, analytics, and deployment pipeline under company-controlled accounts from day one. If a partner disappears tomorrow, you should lose velocity—not ownership of the product.

A simple scoring exercise

Score each workstream from 1 to 5 on four dimensions:

how often requirements will change;
how important the knowledge is to your long-term advantage;
how difficult quality is to verify externally; and
how sensitive the data or workflow is.

High scores point toward hiring or building internal capability. Low scores point toward a well-scoped vendor engagement. If the scores are mixed, start with a short paid discovery sprint, document what you learn, and decide again with better information.

The goal is not to minimize headcount or vendor spend. It is to keep learning close to the business while buying speed where the risk is manageable. Build the capabilities that compound; outsource the work that has a clear finish line.

MVP vs PoC: What Should You Build First?

Rishita Sharma — Thu, 01 Oct 2026 15:15:12 +0000

A proof of concept and a minimum viable product answer different questions. Treating them as the same thing is one of the easiest ways to spend a month solving the wrong problem.

A PoC asks: can this work?

An MVP asks: will a specific group of people use this enough to create a sustainable business?

That distinction matters for both founders and engineering teams.

When a PoC is the right first step

Use a PoC when the biggest risk is technical or operational uncertainty:

Can an unfamiliar API handle the required volume?
Is the model accurate enough on real, messy data?
Can two systems exchange data reliably?
Is the latency acceptable for the workflow?
Can the team meet a security or compliance constraint?

A PoC should be deliberately narrow and disposable. Use representative data, measure the risky part, and set a time limit. If the risk is not retired after that time, you have learned something valuable: the idea needs a different approach or should be paused.

Do not turn a PoC into a product by accident. Production authentication, billing, analytics, polished UI, and support processes are usually distractions at this stage.

When an MVP is the right first step

Build an MVP when you already understand the main feasibility risks and the uncertainty is about behavior. The goal is to create the smallest complete loop for one user type:

A real user has a recognizable problem.
They can complete one useful workflow.
You can observe what happened and ask why.
They have a reason to return, pay, or refer someone.

An MVP can be technically simple without being careless. A spreadsheet behind a small interface, a manual operations step, or a limited integration may be perfectly reasonable if it helps you learn. The important part is that the user receives a real outcome, not a demo that only looks convincing.

A practical decision test

Write down the top three assumptions behind the idea. For each one, label it as either:

Feasibility: can we make it work?
Desirability: does the user actually want it?
Viability: can this become a repeatable business?

If feasibility is the largest unknown, run a PoC. If users have already confirmed the problem and feasibility is understood, build the smallest MVP. If both are uncertain, time-box a technical spike and pair it with five to ten conversations with the target users. Neither artifact replaces customer evidence.

What to measure

For a PoC, measure the risky technical outcome: accuracy, latency, failure rate, cost per transaction, or integration reliability. A successful PoC is evidence, not a feature list.

For an MVP, measure behavior: activation, completion of the core task, repeat usage, time to value, and the quality of user feedback. Revenue is useful, but early on a strong signal can also be a user who changes their workflow or introduces a colleague without being asked.

The best teams keep both artifacts small. A PoC retires technical uncertainty; an MVP creates a learning loop with users. Choose the one that addresses your biggest unknown, and define the evidence you need before writing the first ticket.