The reading order
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1.
The Pre-Series-A AI Startup Hiring Plan: Who to Hire, in What Order, and Why Most Get It Wrong
The full sequence from founding engineer to fifteen, with the comp framework and the mis-leveled hires to avoid.
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2.
From One Engineer to Fifteen: What Co-Founding Taught Me About Engineering Leadership
What changes at each scale boundary. The shift from delivery to leverage to org design.
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3.
How to Manage a 4-Person Engineering Team Without Becoming a Manager
The rituals that work at this size — 1:1 cadence, planning loop, decision-making — and the failure modes when you outgrow them.
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4.
Trust Is the Operating System
The unit is a pod of three to eight people — past eight you stop knowing who's actually stuck and start reading status updates instead of people — so when the team outgrows one pod you repeat it rather than stretch it. Agents run the same operating system as an intern you shouldn't trust off the bat, minus the one part that doesn't transfer: with a person you protect the struggle because that's how they grow, and every agent mistake is a rep for you, not for it.
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5.
A Scared Team Is Your Biggest Attack Surface
A team afraid to report extends every incident by exactly the length of that fear — detection only starts the dwell-time clock once someone tells it to. What breaks a team isn't a strict manager but an unpredictable one, where the same mistake gets a shrug on Tuesday and a public dressing-down on Friday. Blameless postmortems are incident-response infrastructure.
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6.
How I'd Hire a Staff Engineer at an AI Startup
The interview loop, the failure modes, the senior-vs-staff calibration that produces correctly-leveled hires.
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7.
The 'Smallest Possible Slice' Heuristic for Shipping Complex Features
The leverage move that defines senior IC work. Smaller than MVP. Earns the next slice.
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8.
Every Insane Codebase Was Once Rational
A new grad about a year in — running an entire project plus a younger developer reporting to him — asked how he'd know his architecture decisions were right. Every insane codebase is a perfectly sane response to constraints that existed when it was written, so make the decision that's right for the next three to six months. The exception is one-way doors: data model and storage semantics, your public interface, authentication and identity, anything touching money or compliance-relevant records.
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9.
The Perfect Hire Is Killing Your Team
The whiteboard interview rewards memorization and pedigree — the weakest predictors of real performance. Hire for trajectory instead.
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10.
We're About to Stop Making Senior Engineers
The path to senior ran through the grunt work AI now does in one prompt. How to grow architects when the ladder's bottom rungs are gone.
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11.
The Onboarding Playbook for an Agent-Heavy Codebase
Week 1 is read before you write, authorship-aware; week 2 is a small bounded first PR carrying a one-paragraph how-I-built-this note; weeks 5–8 are the real test — reviewing someone else's agent-authored diff, not writing one. Plus the two layers of convention, the one a linter enforces and the one held only in a senior's head, and why a mentorship plan built on boilerplate tickets hands a new hire work the agent would have done in the same PR anyway.
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12.
Performance Reviews When Agents Do the Typing
Commit volume died as a proxy — 4,154 commits in six months of an agent-heavy workflow on one project, more than the previous four years combined. What replaces it: the calls an engineer makes about what not to let the agent do, review quality on work they didn't type, problem selection, verification discipline. Plus the five-question 1:1 script to run in the room instead of pulling up a dashboard.
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13.
A Professional Owns the Whole Outcome
Professionalism isn't process or titles. It's owning the whole outcome — the cost, the failure, the 3am page, the wrong call.
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14.
The Career I Built on Work Nobody Wanted
The filter was never tedium — it's blast radius: does this force me to understand everything downstream of it? Lavender's security program from zero to SOC 2 Type II, the Cognito-to-Auth0 migration covering 225K+ users and $400M+ in assets, InsideTrack's ten services consolidated down to six. Named as a trade, not a hack: years where the visible artifact of your quarter is a checklist.
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15.
Prove the Return or Don't Spend the Time
Time is the one budget you can't refill. Every tool and hour has to show a demonstrable return, or it's a tax on attention.
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16.
How I Triage a New Codebase in 90 Minutes
The 7-step protocol for a useful POV on an unfamiliar codebase in 90 minutes — readme, deps, git log, tests, hot files, auth, incidents.
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17.
What I Check When I Inherit a Vibe-Coded App
The intake order when there's no living person to ask why: dependency manifest before anything else, auth and secrets second, what the tests actually assert rather than how many files pass, the deploy path, and the data model last because it's slowest to audit. GitGuardian's 2026 State of Secrets Sprawl report found Claude Code-assisted commits leaking secrets at a 3.2% rate against a 1.5% baseline across all public GitHub commits. Full rewrite is the answer far less often than instinct suggests.
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18.
How We Cut $350K From Cloud Spend in 6 Months (And What I'd Do Differently)
A real GCP-to-Azure migration: lift-and-shift first, optimize after. The $350K saved, the $50K mistake, and when not to.
Other topic guides
- AI engineering What production AI engineering actually looks like in 2026 — the autonomy ladder for agents, the workflow shift, telemetry, and team sizing.
- Security for startups A guided reading order for startup security — what to read first on SOC 2 as a revenue tool, vCISO hiring, and securing AI-native products.
- Elixir and the BEAM for AI systems Why language choice matters for AI systems — BEAM concurrency for agents, what Go frameworks cost you, and why Elixir is the language AI writes best.