Recent content on Andrés Max
The tests pass. The agent says it’s done, here’s a summary of what changed. You merge it, and for a second it feels like you shipped something. 
 Maybe you did. Nothing in that loop actually told you so, though, and the loop is very good at feeling like it did. 
 There are two questions worth asking about any piece of work. Does this do what I asked for, and should I have asked…
Four tickets went through clean last week. The agents read them, built them, wrote the tests, ran the suite, opened the PRs. I reviewed and merged. That part of the job is basically solved now, and it still feels a little unfair. 
 The fifth one broke the pattern. The ticket said “show the timezone on the matches cards.” Two lines. Any agent on earth could do that in a minute, and…
When founders ask me how I build with AI, they start with the orchestration layer. How many agents, which framework, queues or loops, subagents or one big context. That’s the decoration. 
 The thing that actually decides whether AI ships something or just generates something is the oldest, most boring discipline in engineering. A precise spec, real acceptance criteria, a clear definition…
Most of the SaaS you pay for is a compromise you agreed to because building your own was too expensive. That’s the whole deal. You had a specific way you wanted to work, no time or budget to build a tool for it, so you rented someone else’s idea of how the work should go and adapted yourself to fit. We did this so many times it started to feel like the natural order of software. It…
Every prioritization framework I’ve ever used was a hedge against an expensive mistake. RICE, scoring, the quarterly roadmap argued over for two days. The whole point was to be sure before you spent a sprint, because the sprint was the thing you couldn’t get back. Deliberation was cheap relative to building, so you deliberated. 
 That trade just flipped. 
 Building got cheap.…
For about two years, building with AI felt free. It wasn’t. Someone was just paying for it. 
 Now the bill is showing up. Uber capped how much its employees can spend on AI after blowing through the budget in four months. Companies are watching their token bills climb the way they used to watch AWS bills, except faster and with less to show for it. The subsidies that made every prompt…
I sold Ideaware in April. 
 Fifteen years of one company. I started it with a stubborn idea about how good products should feel. By the end, I’d worked with hundreds of teams, hired hundreds of people, placed hundreds more, and built something I’m still proud of every time I look back. The sale closed in April, and I haven’t stopped thinking about that fact since. 
 This…
I caught myself last week telling a founder he was at Level 2 of agentic engineering. He looked at me like I’d made up the levels on the spot. I had, kind of. But the more I sat with it, the more the levels felt real, because the gap between Level 2 and Level 4 is the difference between “using AI” and running a different kind of business. 
 A few weeks ago I wrote The AI…
There’s an unspoken rule in product design that nobody writes down but every user enforces: the moment you came for needs to happen fast. Not eventually. Not after a sidebar loads and a workspace initializes. Fast. 
 That gap has a name in my head: time to access. It’s the distance between intention and action. And it’s the thing most products quietly lose on. 
 Most…
Most mornings I’m running four or five parallel workstreams before lunch. One agent is building a feature on a project, another is reviewing a PR, another is drafting specs for the next sprint. I’m writing requirements, reviewing output, making judgment calls. I’m not writing most of the code anymore. 
 Someone put a name to this recently. A tweet with 210,000 views defined…
I was riding the wave like everyone else. Open source AI agents, personalities on Telegram, server integrations, multi-agent orchestration. The promise was real and I bought in hard. I even built something on top of it: Clawdeck , an open source kanban board for managing AI agents and their tasks. A shared board where you and your agents could work side by side. It got 300, maybe 400 stars on…
I shipped four products in the past year. tini.bio , lst.so, gratu , nod.so. All of them built with AI writing most of the code . Claude Code handles my Rails controllers, my Stimulus controllers, my migrations. It’s fast. Genuinely fast. 
 So can AI replace developers? I’ve been testing that question with real products and real users for a year now. Here’s what actually…
I’ve seen six Lovable prototypes this month. All of them worked. None of them felt like products. And that gap, between working and feeling like something worth using, is where taste lives. 
 Built in a weekend, shown to investors, got some early feedback. Great for proving the idea. Not even close to something you’d actually want to use. 
 The screens look like PowerPoint…
In the last two weeks I’ve had a handful of conversations with founders. Different industries, different stages, different products. But the same thing kept coming up. 
 Teams that refuse to adopt AI tools don’t just slow down. They force founders to replace them with smaller, faster teams that already build this way. 
 They all get AI. They’ve used it. They’ve seen…
You built it in a weekend. Cursor, Bolt, v0, maybe Replit. It runs on your laptop, it looks good in a demo, and investors leaned in when you showed it. 
 Now what? 
 This is the moment most founders hit a wall they didn’t see coming. The prototype works. The product doesn’t exist yet. And the gap between those two things is where most ideas quietly die. 
 The prototype trap…
I spent 18 years estimating how long products take to build. Story points. T-shirt sizing. Sprint planning. Quarterly roadmaps. Gantt charts that nobody believed but everyone pretended to follow. 
 All of that is useless now. 
 Not because estimation was always wrong (it was, but that’s a different article). Because the thing we were estimating changed so fundamentally that the…
Every founder I talk to has the same gap in their operation. They know their market. They can sell. They can raise. They can build relationships and close deals. But the product sits in no-man’s land. 
 Not because they don’t care about it. Because nobody owns it. 
 They’ve tried agencies. The agency delivered something that looks nothing like what they described.…
Every startup blog will tell you the same thing about idea validation: validate before you build. Do 20 customer interviews. Run surveys. Create a landing page. Collect email signups. Pre-sell before writing a line of code. 
 That playbook made sense in 2020. It doesn’t anymore — not for validating a startup idea, not for validating a business idea, not for validating software ideas of…
For 20 years, building a software product meant the same thing. Hire a team. Write a spec. Sit through standups. Wait months. Spend six figures. Hope it works. 
 That playbook is dead. 
 Not dying. Not evolving. Dead. And most founders haven’t realized it yet. They’re still hiring teams of 20, still running sprints, still budgeting $500k for an MVP, still waiting six months to…
I shipped five products recently. All within about six weeks. Different stacks, different users, totally different problems. Two of them are already making money. 
 I know that sounds like the setup for a “here’s what I learned” thread. It’s not. I’m still processing it honestly. I didn’t plan to build five things at once. I just kept finding problems I…
The hardest part of product isn’t deciding what to build. It’s deciding what not to build. When your biggest customer threatens to churn without feature A, your sales team can’t close deals without feature B, and your engineers say the codebase will collapse without addressing technical debt C, you don’t have a prioritization problem. You have an emotional problem. 
…
A 5-person team in 2026 can ship what a 50-person team shipped in 2016. AI has compressed the development curve dramatically. The question every founder and engineering leader is asking: do large software teams still make sense? 
 This is the real story of AI’s impact on software engineering team sizes in 2026 — not the headline version. 
 After scaling teams from 3 to 80+ people…
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Most AI products fail twice: once when the technology doesn’t work, and again when nobody wants it anyway. Traditional validation focuses on market risk. Will customers pay? AI products add technology risk. Can AI actually do this reliably? 
 I’ve seen founders spend $50K+ building AI products that either don’t work technically or don’t solve problems anyone has. Both…
Everything you learned about product management is wrong for AI products. Roadmaps? Useless when underlying capabilities change every few weeks. Specs? Meaningless when you can’t predict what the model will output. User stories? Incomplete when AI behavior is probabilistic, not deterministic. 
 I’ve spent the last few years building AI-powered products, and the hardest part…
Your startup doesn’t have an AI problem. It has a product problem that might be solved with AI. This distinction is everything. Get it wrong, and you’ll spend six months building AI features that don’t move your business forward. Get it right, and AI becomes a genuine competitive advantage. 
 Every founder I talk to now has “AI” somewhere in their plans. Add AI to…
The best product strategy isn’t a list of features to build. It’s a clear answer to one question: what change are you creating in your customer’s life? Most early-stage founders confuse product strategy with product planning. They create detailed roadmaps full of features, launch dates, and technical specifications. Then they wonder why they’re busy shipping but not…
The main reason AI projects fail is simple: companies start with the technology instead of the problem. 42% of companies scrapped their AI initiatives in 2025—not because AI doesn’t work, but because they built solutions to problems that didn’t exist. The fix? A 30-day validation framework that forces you to prove value before you build. 
 You’ve seen it happen. Maybe…
The fastest way to build a lean MVP is to build the smallest experiment that tests your riskiest assumption—not a scaled-down version of your vision. Most lean MVPs fail not because the idea is bad, but because founders build the wrong thing, take too long, or run out of money before finding product-market fit. 
 After helping dozens of startups build their first products over 18 years,…
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The fastest way to ship AI products is with a pod—a small, complete team that owns outcomes—not traditional hiring. A 3-4 person pod (ML engineer + full-stack dev + designer/PM) costs 60-70% of equivalent salaries, ships in 12 weeks instead of 6+ months of hiring, and lets you validate before committing to full-time hires. 
 I’ve been building teams for 15 years. I’ve helped…
Your first product hire should complement your weaknesses, not duplicate your strengths. If you’re a technical founder, hire a product designer first; if you’re non-technical, you need a technical co-founder or CTO before anyone else. The hardest part of building a product isn’t writing code—it’s assembling the best full-time product team to write that code. 
 After…
Dribbble broke UX design by rewarding beautiful screenshots over functional user experiences. The platform created a generation of “visual-first” designers who skip user research, flows, and validation—jumping straight to pixel-perfect mockups that look great in portfolios but fail in production. The fix: always design user flows first, visual polish last.
Trusth those who have walked the path, not those who sell you hard on a promise.
When was the last time you were productive for 8 hours a day sitting in front of your computer?
Having “on-time” as your team’s (or project) success metric is a dangerous endeavor.
For over 12 years I’ve worked with SaaS product teams. Many have been successful in launching and generating revenue, others failed to ship. It all comes down to your product roadmap.
The best competitive strategy is to ignore your competitors and obsess over your customers instead. After 18 years and 5 startups, I’ve watched competitor-focused companies lose to customer-focused ones every single time. The companies that win long-term build for users, not rivals—and here’s exactly how to do it.
I’m Andrés Max. 5x founder. 18 years building products, teams, and companies. Today I work with founders and product leaders one-on-one as their built-in product partner, and I build AI-native products at mx.works . 
 What I do 
 I advise founders and product leaders on: 
 
 Product strategy: what to build, what to cut, what to ship 
 Product design and UX 
 AI…