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TL;DR: The tools that win in 2026 aren't the ones with the most features. They're the ones that match how a team actually makes decisions when nobody's watching. Stop looking for the "best all-in-one platform" and start architecting around three layers: communication, execution, and intelligence coordination.
It's a familiar story by now, told slightly differently by every team that's lived through it: a 30-to-50-person agency migrates everything onto "the only AI work platform you'll ever need," spends a few weeks and a few thousand dollars doing it, and is quietly back to a patchwork of Slack, Notion, and a spreadsheet within two months. The tool wasn't broken. The assumption was.
The assumption: that "all-in-one" means "better." That fewer tabs equals faster work. That if a platform has AI on every button, a team will suddenly coordinate like a unit. None of this holds up. What actually determines whether AI workflow tools accelerate a team or slow it down is something the comparison blogs skip entirely: the coordination pattern the team already has, whether anyone's named it or not.
The tools that win in 2026 aren't the ones with the most features. They're the ones that match how a team actually makes decisions when nobody's watching.
⚡ Key Takeaways
"Best all-in-one platform" is the wrong question. The stacks that hold up past 12 people run three separate layers — communication, execution, and AI coordination — not one tool trying to do everything.
Rule-based and context-based automation solve different problems. Zapier-style tools handle predictable triggers; AI agents like Coworker or monday.com's Agents handle judgment calls. Most teams need both.
Gartner expects 40% of enterprise apps to carry task-specific AI agents by the end of 2026 — and also expects over 40% of agentic AI projects to be canceled by 2027. Adoption and failure are rising together; architecture is what separates them.
Price gaps between tools are usually tier gaps, not vendor gaps. monday.com Standard and ClickUp Business land within a few dollars of each other once you compare equivalent feature depth.
The biggest adoption blocker is rarely the tool. It's that visible, automated coordination threatens whoever currently holds informal control over information flow.
This isn't a listicle. Below is why the "best AI workflow tool" framing is a trap, what the 2026 landscape actually looks like for teams who need to move fast, and how to build a stack that doesn't collapse the moment you hire your 15th person — along with which specific tools are worth your time right now, priced and rated against what I could actually verify rather than what circulates in older comparison posts.
"Just Pick One Platform" Is the Most Expensive Advice in Collaboration
Every major vendor — ClickUp, monday.com, Notion, Asana — now markets itself as an "AI work platform." The pitch is seductive: one subscription, one login, one place where everything lives. The reality is that teams which actually try full consolidation tend to hit a wall around 12 people.
Here's what happens. A team consolidates chat, docs, tasks, and whiteboards into one platform. For a few weeks, everyone's excited. Then the designer needs Figma-level prototyping. The engineer needs Jira-level sprint tracking. The sales lead needs a CRM that doesn't feel like a database bolted onto a task manager. The "one platform" now has 40-plus integrations, several syncing bidirectionally and duplicating notifications. The "streamlined" stack is a patchwork with better marketing.
On ease-of-use specifically, monday.com has a real, repeatedly-documented edge: it scores roughly 9.0–9.1 out of 10 on G2 for ease of use, against ClickUp's 8.1–8.5. But on overall satisfaction the two are close enough to call a tie — both sit around 4.7 out of 5 on G2, and ClickUp actually edges ahead in some 2026 category rankings for power users. monday.com's visual simplicity, which makes it genuinely faster to adopt, becomes a ceiling once a team needs custom operational logic. ClickUp's flexibility, which intimidates new users, becomes an asset once a team is managing 200-plus tasks with dependencies across five departments. The "best" tool depends on whether the problem is adoption friction or operational complexity — and most growing teams have both, at different stages.
Notion sits in a different category. It isn't trying to be a project manager — it's a programmable workspace where a team builds its own system. That freedom is why creators and startups love it. It's also why operations teams tend to outgrow it: Notion's automation is lighter than monday.com's or ClickUp's, and tasks generally need to be entered manually rather than triggered by an external event landing in an inbox or a form. If the workflow is "think, write, organize," Notion is close to unmatched. If it's "receive request, route to team, track SLA, escalate if blocked," Notion will fight back.
⚠️ The Trap: The "one platform" narrative serves vendor revenue more than team velocity. Every major platform loses money on its free tier and makes it back on enterprise upsells and add-ons — AI credits, premium connectors, Copilot-style add-ons priced separately from the base seat. The more a team consolidates onto one vendor's full ecosystem, the more expensive it becomes to leave later. That isn't a conspiracy; it's just how the incentive is built.
What the Data Actually Says About Tool Consolidation
Vendors use "knowledge workers switch apps constantly" statistics to argue for consolidation. But the more useful finding, from decades of attention research by UC Irvine informatics professor Gloria Mark, isn't about app-switching frequency — it's about recovery cost. Mark's research, most recently collected in her 2023 book Attention Span, has repeatedly found that it takes an average of 23 minutes and 15 seconds to fully return to a task after an interruption, with people typically completing two unrelated tasks in between. An all-in-one platform doesn't fix that if a team still makes decisions in side-channel DMs and updates the system of record three days later — the tool changed, but the reconstruction tax didn't.
The platforms that actually cut that tax aren't necessarily the ones with the most features. They're the ones with the best ambient awareness — surfacing what changed, why, and who needs to know, without someone manually writing a status update. This is where AI features in 2026 are making a real difference, and it's what the feature-count comparison tables miss.
The 2026 AI Stack That Actually Works: Layered, Not Consolidated
The pattern that consistently holds up, across teams from roughly 4 to 200 people, is a three-layer architecture: a communication backbone, a work execution layer, and an intelligence coordination layer. Each layer has one primary tool. Everything else is an integration or a specialized satellite.
┌─────────────────────────────────────────────────────────────┐
│ 🧠 INTELLIGENCE COORDINATION LAYER │
│ AI agents, automation engines, cross-tool context sync │
├─────────────────────────────────────────────────────────────┤
│ ⚙️ WORK EXECUTION LAYER │
│ Project management, task tracking, docs, whiteboarding │
├─────────────────────────────────────────────────────────────┤
│ 💬 COMMUNICATION BACKBONE │
│ Real-time messaging, async video, meeting infrastructure │
└─────────────────────────────────────────────────────────────┘
This is what it tends to look like in practice, built from real, current pricing and product fit rather than any single client story:
- A Series B fintech running Slack + monday.com + Coworker AI
- A 12-person content agency on Slack + Notion + Zapier
- A 90-person e-commerce operation on Microsoft Teams + Asana + Power Automate
The specific tools vary by ecosystem and budget. The three-layer shape doesn't.
Layer 1: The Communication Backbone
This is where decisions get made in real time — not where they're documented, where they're actually made, in the 30-second thread or the 4-minute huddle. If this layer is broken, nothing else matters.
💬 Slack
Pro runs about $7.25/user/month, Business+ about $15/user/month (both annual). Basic AI — thread summaries, huddle notes — now ships on every paid plan; the deeper Advanced AI search and workflow generation is gated to Business+. Best for teams that live in integrations.
🔷 Microsoft Teams
Bundled into Microsoft 365; if a team already pays for it, Teams is close to free. Copilot is a separate add-on at $30/user/month on top of a qualifying M365 license — the most capable AI layer of the three, and the most expensive one.
📹 Zoom Workplace
Pro starts around $13–14/user/month. AI Companion — summaries, action items, chat drafting — is included at no extra charge on every paid plan, which is a real differentiator against Copilot's separate $30/seat charge. Async video culture can cut a meaningful share of status meetings if the team actually adopts it.
Rule of thumb:
- Under 20 people and not in the Microsoft ecosystem: start with Slack.
- Over 50 or in a regulated industry: Teams is hard to beat on compliance (SOC 2, HIPAA, GDPR, FedRAMP are all standard at the enterprise tier).
- Video-first team: Zoom's bundled AI Companion makes it the cheapest way into meeting intelligence at scale.
Layer 2: The Work Execution Layer
This is where tasks get tracked, documents get written, and projects get managed. The common mistake is choosing by feature count rather than decision visibility — how easily anyone can see what's blocked, who owns it, and what happens next.
| Tool | Best For | AI Approach | Entry Paid Tier* | G2 Score |
|---|---|---|---|---|
| monday.com (Fastest to Adopt) | Visual coordination, non-technical teams | Sidekick, Agents, and AI Blocks across the suite | $9/seat/mo (Basic) | ★★★★★ 4.7/5 |
| ClickUp (Power Users) | Complex ops, agencies, software teams | ClickUp Brain (add-on) + agent workflows | $7/seat/mo (Unlimited) | ★★★★★ 4.7/5 |
| Notion (Knowledge-First) | Creators, startups, docs + light PM | Notion AI: Q&A, writing, workspace search | $10/seat/mo (Plus) | ★★★★☆ 4.6/5 |
| Asana (Strategic PM) | Cross-functional projects tied to company goals | Asana Intelligence: status rollups, smart suggestions | $10.99/seat/mo (Starter) | ★★★★☆ 4.4/5 |
| Airtable (Data-Driven) | Marketing ops, content calendars, relational data | AI field type for generation, classification, summarization | $20/seat/mo (Team) | ★★★★☆ 4.6/5 |
*List pricing, billed annually, verified against vendor pricing pages and Vendr's benchmark data in August 2026. Monthly billing runs 20–40% higher across all five. Confirm current rates before budgeting — several of these tiers changed in the past year.
Once tiers are compared like-for-like, the price story is less dramatic than it looks. For a 15-person team, monday.com's Standard plan — the tier most teams actually need for real automation — runs $12/seat, or $180/month. ClickUp's Business tier, which unlocks comparable automation depth, runs the same $12/seat, or $180/month. ClickUp's cheaper Unlimited tier ($7/seat, $105/month) undercuts monday.com's entry Basic tier ($9/seat, $135/month), but Basic is thinner on automation. Step up to monday.com's Pro tier — the one that adds time tracking and private boards — and it's $19/seat ($285/month), noticeably pricier than anything ClickUp offers below Enterprise. The gap isn't really "monday.com costs more." It's "which tier does your team actually need to reach comparable depth," and that depends on how much configuration the team is willing to do to get there.
Asana deserves a specific mention for a feature most teams ignore until they need it: Goals and Portfolios, available from the Advanced tier ($24.99/seat/month annual — more than double Starter's $10.99). If projects need to connect to company OKRs — and at some point they will — Asana is the tool in this list where that connection feels native rather than bolted on. The jump to Advanced is real money, but Portfolios alone tends to justify it for anyone managing five or more concurrent projects.
Layer 3: The Intelligence Coordination Layer
This is where 2026 diverges from every previous year. AI is no longer just a feature inside individual tools — it's becoming a coordination layer between them. The platforms that matter here don't replace a stack; they connect it.
01 — Coworker: Context-Based Automation
Roughly $30/user/month for CRM-connected agents. Joins meetings, reads what happened, and executes across Salesforce, Jira, Slack, HubSpot, and Gmail — updating deal stages, drafting follow-ups, flagging stale pipeline — without a human writing the trigger rule first. This is the practical difference between automation and judgment: it decides what needs to happen based on context, not a predefined "if this, then that."
02 — Zapier: Rule-Based Breadth
Pricing is task-volume-based, not per-seat: Free covers 100 tasks/month, Team plans start around $69/month for 2,000 tasks. Still the broadest integration library in the category. Best for operations teams with well-defined, repeatable processes rather than judgment calls.
03 — Make: Visual Complex Logic
From roughly $9–12/month (Core tier, annual). Make renamed its billing unit from "operations" to "credits" in 2025, but the mental model is unchanged: every module call costs a credit. The strongest visual builder for branching, multi-step logic with real error handling. The interface can overwhelm non-technical users.
04 — Microsoft Power Automate + Copilot
$15/user/month for the Premium plan; Copilot layers on top at the same $30/user/month as Microsoft 365 Copilot elsewhere. Describe a workflow in plain English and Copilot drafts it. Deeply integrated into M365 — the lowest-friction intelligence layer if already committed to that ecosystem, and not the place to start otherwise.
05 — n8n: Self-Hosted Control
Free and unlimited self-hosted (Community Edition); cloud plans from about $24/month for 2,500 executions. Open-source with AI agent nodes for LLM-powered decision-making. Built for engineering teams that want data residency and infrastructure control — not for business users who don't want to think about servers.
The critical point: most teams need both rule-based and context-based automation. Zapier or Make handle the predictable work ("when a form is submitted, create a task and post to Slack"). Coworker or a comparable agent handles the ambiguous work ("after this client call, figure out what actually needs to happen and do it"). Relying on only one is like keeping a single tool in the box for every job.
What Actually Breaks at Scale (And How to Prevent It)
Gartner expects 40% of enterprise applications to ship with task-specific AI agents by the end of 2026, up from under 5% at the start of 2025. The AI agent market itself is projected to grow from $7.84 billion in 2025 to $52.62 billion by 2030 — a 46.3% compound annual growth rate, according to MarketsandMarkets, with several other research firms landing in the same general range. That sounds like unambiguous good news. It's also a warning: Gartner separately predicts that more than 40% of agentic AI projects will be canceled by the end of 2027, citing escalating cost, unclear business value, and inadequate risk controls — and that roughly 89% of AI agent pilots never reach production in the first place.
Here's what tends to break when AI agents multiply across a stack without any architecture governing them:
Agent collision: A CRM agent updates a deal stage. A project-management agent sees the change and creates a task. An automation platform sees the task and posts to Slack. A Slack summary bot picks it up and notifies the whole channel — including the person who made the original update. Three seconds of real work, six redundant notifications.
Context drift: Each agent operates on its own slice of data. The CRM agent knows the client said budget is tight. The project agent knows the deadline moved. The chat agent knows the team is frustrated. No single agent sees all three, so no agent connects the dots that a person would: this needs a scope conversation, not another automated nudge.
Permission sprawl: Agents need broad access to be useful; broad access cuts against least-privilege security practice. Gartner puts real numbers on this gap — only about 21% of organizations report a mature governance model for agentic AI, meaning roughly four in five are scaling agents without one. In a regulated industry, that's not a trade-off to accept quietly; it's a compliance gap waiting to surface in an audit.
The fix isn't fewer agents — it's orchestration: a coordination layer that knows what every agent is doing, resolves conflicts, and keeps an audit trail. This is a large part of why enterprise iPaaS platforms are gaining traction in larger organizations even though they're not the tools anyone gets excited to demo. They're infrastructure, and infrastructure is what keeps agentic AI from becoming its own source of noise.
The Async Video Layer Everyone Ignores
Loom isn't a collaboration platform; it's a communication modifier. It replaces a 15-minute status meeting with a 3-minute video the recipient can watch at 1.5x speed. AI-generated summaries and searchable transcripts mean the information survives past the moment it was recorded, unlike a meeting that evaporates the second it ends.
⚠️ Worth Knowing Before You Budget: Loom's Business plan now runs about $15–18/user/month, Business + AI about $20–24/user/month (Atlassian, which acquired Loom in 2023, has been migrating billing onto its own systems). Part of that migration: the free "Creator Lite" viewer role is being phased out, and existing free viewers on some workspaces are being auto-upgraded to full paid seats after a grace period. Teams have reported year-over-year bills jumping several times over purely from that seat reclassification — worth checking your workspace's current roster before renewal, not after.
The honest constraint: Loom needs cultural buy-in. Some people will never watch a video when they could skim text; others will record eight-minute monologues when ninety seconds would do. Teams that make it work set a hard rule — no video over three minutes without a written summary in the description — which respects both preferences and keeps the content searchable.
Specialized Tools That Earn Their Place
Not every tool belongs in the core stack. Some are worth adding as satellites:
🎨 Figma
Non-negotiable for design teams. Real-time co-design, Dev Mode for handoff, FigJam bundled into every paid seat. Professional runs about $15/editor/month (annual); Organization jumps to roughly $45–55 for SSO and org-wide design systems. Skip it entirely if the team doesn't do UI/UX.
🖊️ Miro
Infinite-canvas whiteboarding, thousands of templates. Starter runs about $8/user/month, Business roughly $16–20 (annual) and adds SSO plus deeper Jira/Asana integration. Best for remote workshops and strategy sessions — watch for auto-billing when viewers get added as "members."
📊 Coda
Documents that behave like apps. Pricing is per "Doc Maker" — the people who build docs — not per viewer or editor, which is a genuinely different (and often cheaper) model than Notion's or Airtable's flat per-seat pricing. Pro runs about $10/Doc Maker/month, Team about $30 (annual). Good fit for ops teams building internal tools without developers.
How to Choose a Stack Without Regret
Skip the feature matrices. Answer these four questions in order:
1. Where do decisions actually happen?
If a team makes calls in threads, the communication backbone is Slack. If it makes them in weekly video standups, it's Zoom. If it makes them in document comments, it's Google Docs or Notion. Whatever tool hosts the actual decisions is the backbone; everything else serves it.
2. What was the most expensive coordination failure last quarter?
A missed deadline? A client escalation? Duplicated effort? Whichever tool would have prevented that specific failure is the execution-layer priority — not the tool with the best G2 score, the tool that closes the actual gap.
3. How much ambiguity is in the work?
If most of it follows predictable patterns — content production, support tickets, sales outreach — rule-based automation (Zapier, Make) is sufficient. If a meaningful share requires judgment calls — client strategy, product prioritization, creative direction — the team needs context-based AI (Coworker, monday.com Agents) or it's just automating the wrong things faster.
4. What's the real budget per person per month?
Include the hidden costs: AI add-ons (roughly $8–30/user/month depending on vendor), automation platforms ($10–100+/month), training time (weeks of reduced output while people learn the new system), and the cost of switching if the first choice is wrong. A "free" tool that eats forty hours of setup time isn't actually free.
Team Profile Quick Reference
| Team Profile | Illustrative Stack | Monthly Cost (15 people)* | Trade-off |
|---|---|---|---|
| Startup / Creator (<10 people, knowledge-first) | Slack Free + Notion Plus + Loom Free | ~$150 | Weak automation, manual task entry |
| Growth Agency (10–30 people, client work) | Slack Pro + monday.com Standard + Zapier Team | ~$460 | Less raw flexibility than ClickUp, faster to onboard new hires |
| Software Team (15–50 people, sprints) | Slack Pro + ClickUp Business + Make | ~$400 | Steeper learning curve, deeper long-run control |
| Microsoft Enterprise (50+ people, regulated) | Teams + Asana Advanced + Power Automate + Copilot | ~$1,200 | Highest compliance ceiling, highest per-seat cost |
| AI-Native Team (experimenting with agents) | Slack Pro + monday.com Pro + Coworker + n8n Cloud | ~$935 | Most capable, needs someone accountable for governance |
*Rough monthly total for a 15-person team on the named tiers, annual billing, before task/credit overages. Treat as a planning estimate, not a quote — confirm against each vendor's live pricing page.
A Tool Worth Naming Directly: Why Trello Slipped
Trello is still excellent for visual simplicity, and for years it was the reasonable default for small teams. That calculus has shifted: in 2026, a tool with minimal native AI means a team is manually doing work — status rollups, routing, follow-up drafting — that competitors now do automatically. For a five-person team, the few dollars saved per seat rarely outweighs the hours lost to manual updates and the absence of intelligent routing. It's not that Trello got worse. It's that the bar it's being measured against moved.
The same logic applies to free tiers generally past about eight people. Slack Free's 90-day message history, ClickUp Free's storage cap, Miro Free's 3-board limit — these stop being savings and start being a tax on active collaboration. Pay for whatever removes friction, not whatever creates it.
The Real Reason Teams Resist New Tools
It's rarely the learning curve or the price. It's that new tools threaten existing power structures. The person who owns the Notion workspace has status. The person who knows the Asana automation rules has job security. The person who schedules the meetings controls the calendar. An AI coordination layer that makes decisions visible to everyone threatens all three — quietly, and usually without anyone saying so out loud.
That's a meaningful part of why so many AI workflow rollouts stall after the pilot: not because the technology failed, but because the team's informal social contract was never renegotiated. Before buying anything, it's worth asking directly: who currently controls the information flow, and what happens to their role when it's automated? Without an answer, a rollout will meet passive resistance no onboarding tutorial fixes.
Teams that succeed don't just implement tools. They implement coordination contracts — explicit agreements about who owns what, where decisions get made, and what an AI agent is and isn't allowed to do on its own. That sounds like overhead. It's actually what makes everything else fast.
If a collaboration stack is genuinely working, it should be possible to delete any single tool and still know who is doing what, why, and by when. If that's not true, it's not a workflow being run. It's a dependency.
If coordination contracts matter more than tool features, then the entire genre of "best AI workflow tool" roundups is quietly making teams worse by encouraging tool-first thinking. The better question isn't "which platform has the most AI features?" It's "which platform lets us enforce our own coordination contract without constant manual upkeep?" Answer that, and the tool choice mostly falls out on its own.
FAQ
What's the single best all-in-one AI work platform in 2026?
There isn't one, and that's the point of this piece. Every "all-in-one" platform is strongest at one job (visual coordination for monday.com, operational depth for ClickUp, flexible documentation for Notion) and weaker at the others. Teams that hold up past roughly 12 people run a communication tool, an execution tool, and a separate AI coordination layer — three tools, not one.
Is monday.com or ClickUp better for a small team?
For pure speed of adoption, monday.com's ease-of-use edge on G2 (roughly 9.0–9.1 vs. ClickUp's 8.1–8.5) is real and consistent across sources. For a team that expects to need deep customization within a year, ClickUp's flexibility usually pays off despite the steeper learning curve. Overall satisfaction scores are close enough on G2 (both around 4.7/5) that this is a fit question, not a quality question.
Do I need a separate AI automation tool if my project management tool already has built-in AI?
Usually yes, for a specific reason: built-in AI (Notion AI, Asana Intelligence, ClickUp Brain) mostly operates inside that one tool's data. Cross-tool automation — reading a meeting, then updating a CRM, then creating a task in a different system — needs either a rule-based platform (Zapier, Make) or a context-aware agent (Coworker) that can read and write across multiple systems.
What's the real difference between Zapier, Make, and n8n?
Zapier has the broadest integration library and the simplest setup, billed by task volume. Make is more powerful for branching, conditional logic at a lower cost per action, billed by credits. n8n is open-source and free to self-host with unlimited executions, but requires someone comfortable running infrastructure. None of the three currently does context-based judgment the way an AI agent platform does — they execute rules, not decisions.
Is it safe to give an AI agent access to Slack, email, and a CRM at the same time?
It's common, but Gartner's data suggests most organizations aren't governing it well — only about 21% report a mature governance model for agentic AI. Before granting broad access, it's worth defining explicitly what an agent can do autonomously versus what needs human approval, and keeping an audit trail of what it actually did. Broad access without that structure is the permission-sprawl problem described above, not a hypothetical one.
How much should a 15-person team budget for a full AI-enabled stack?
Realistically somewhere between $400 and $1,200 a month depending on ecosystem and how much AI automation is layered in, per the team-profile table above. The single biggest swing factor is whether Microsoft 365 Copilot ($30/user/month) is in the mix — it roughly doubles the AI-layer cost compared to Zoom's bundled AI Companion or Slack's included basic AI.
About This Piece
This was rebuilt in August 2026 against an earlier July 2026 draft. Rather than carry the previous numbers forward, I checked current pricing directly against vendor pricing pages and third-party benchmark data (Vendr, G2) for every tool named, since several of these vendors changed tier structures or prices within the past year — monday.com's and ClickUp's figures in particular, since the earlier draft's internal math didn't hold together on inspection.
Two figures from the earlier draft couldn't be traced to a credible source and were dropped rather than repeated: an "80% of enterprise apps will have AI agents by 2026" statistic (Gartner's actual agent-specific figure is 40%; 80% refers to a separate, 2023-vintage prediction about general GenAI API usage, which this piece conflated) and a "60% of deployments stall at pilot" claim, replaced above with Gartner's own sourced prediction on agentic AI project cancellations and pilot failure rates. The team examples in the three-layer section (the fintech, the content agency, the e-commerce operation) are illustrative composites built from verified pricing and product fit, not specific client engagements.
SaaS pricing changes often enough that several figures here shifted even within the research window for this piece. Treat every number as an August 2026 snapshot and confirm against the vendor's own pricing page before committing a budget.
Primary Sources
- AI agent market size and growth rate: MarketsandMarkets
- Enterprise AI agent adoption and project cancellation forecasts: Gartner, via compiled 2026 statistics and a one-year retrospective on the prediction
- Interruption-recovery research: Gloria Mark, UC Irvine, Donald Bren School of Information and Computer Sciences
- Platform ratings: G2 and independently verified monday.com/ClickUp comparison data
- Pricing verified against vendor pages and Vendr's benchmark marketplace across individual tool pages for monday.com, ClickUp, Notion, Asana, Airtable, Slack, Figma, Miro, and Coda, plus Slack's own plan-change documentation, Coworker's product documentation, and current Zapier, Make, n8n, and Power Automate pricing pages.
Top comments (2)
Sorry, but that's hard to read - even when I click the "maximize" button, the text goes off the right side of my monitor, by 50% or so ... are you assuming a 32 plus inch monitor? This stopped me from reading it ...
P.S. thanks, that's much better - the previous version looked like it was only for AI agent consumption! 😄