Liam Walsh

Ironically, I think the shift to AI should actually increase 100x the thought and care you put into framework and toolkit selection even if it takes 1/100th of the time to implement.

Tennis players live 9.7 years longer than sedentary people. Not 9.7 months. 9.7 years. Nearly a decade. The Copenhagen City Heart Study tracked 8,577 people for 25 years and ranked every sport by how much life it adds. Badminton: 6.2 years. Soccer: 4.7. Cycling: 3.7. Swimming: 3.4. Jogging: 3.2. Tennis almost triples jogging. A separate study of 80,000 adults found racket sports cut all-cause mortality by 47% and cardiovascular death by 56%. Swimming hit 41%. Aerobics hit 36%. The question is why racket sports destroy everything else. Three mechanisms stack on top of each other. First, the physical demands. A tennis rally requires explosive sprints, lateral cuts, and sustained aerobic output. You're training fast-twitch and slow-twitch muscle fibers simultaneously. Most cardio only trains one system. Second, the cognitive load. You're reading spin, predicting angles, adjusting position, and executing motor patterns in real-time. Your brain is solving spatial puzzles at 80+ mph. That hand-eye coordination and strategic processing builds neural connections that protect against cognitive decline. Third, and this is the one researchers keep coming back to: you literally cannot play alone. Every racket sport requires another person on the other side of the net. That forced social interaction triggers neurochemical benefits that solitary exercise cannot replicate. Strong social connection alone increases your chance of longevity by 50%. Jogging is you and your thoughts. Tennis is you, a strategic opponent, and a community. Dr. Daniel Amen is right. The data is overwhelming. If you want the single highest-ROI activity for a longer life, pick up a racket.

at this point anthropic is just a military contractor

so many tools and apis and ai thingies and nobody is shipping anything substantial, the fumble is incredible

I don’t review code written by agents. I measure things like test coverage, dependency structure, cyclomatic complexity, module sizes, mutation testing, etc. Much can be inferred about the quality of the code from those metrics. The code itself I leave to the AI. Humans are slow at code. To get productivity we humans need to disengage from code and manage from a higher level.

BREAKING: Anthropic's new model, Claude Mythos, is so powerful that it is not releasing it to the public, per NYT, Instead, it is starting a 40-company coalition, Project Glasswing, to allow cybersecurity defenders a head start in locking down critical software.

Uber gave 5,000 engineers access to Claude Code in December. By February, usage had nearly doubled. By April, the CTO told the company they'd burned through the entire annual AI budget. The adoption curve tells you everything about what happened. In December 2024, 32% of Uber's engineers were using Claude Code. By February 2026, that number was 63%. That's not a gradual rollout. That's a product so useful that engineers pulled it into their workflow faster than finance could model the spend. Uber has about 34,000 employees. Engineering is roughly 15% of that headcount, somewhere around 5,100 people. At enterprise API pricing, Claude Code runs $100 to $200 per developer per month on Sonnet alone. But that's the subscription math. The real number is token consumption, and Uber's engineers aren't building hello-world apps. They're building rider-driver matching algorithms, dynamic pricing engines, and real-time logistics across 70+ countries. Every one of those tasks eats context windows for breakfast. The scale of what these engineers are actually doing with AI is wild. 92% of Uber's developers use AI agents monthly. 65 to 72% of code written inside IDEs is now AI-generated. 11% of all pull requests are opened by agents, not humans. The company's AI code review system, uReview, analyzes over 90% of the 65,000 diffs Uber ships per week. AI-related costs at Uber are up 6x since 2024. CTO Praveen Neppalli Naga's quote was "I'm back to the drawing board." That's the CTO of a $144 billion company admitting that the tools work so well his team can't afford to keep using them at this rate. Here's the part nobody is pricing in. Anthropic's Claude Code hit $2.5 billion in annualized revenue by February 2026. That's up from $1 billion in November 2025. The fastest enterprise software ramp in history, and a huge portion of that growth is coming from exactly this pattern: companies deploy Claude Code, engineers love it, usage explodes, budgets evaporate. Uber won't be the last company to have this conversation. The average Claude Code developer burns about $6 per day. Multiply that across thousands of engineers running complex agentic workflows, spawning sub-agents that each maintain their own context windows, and the math compounds fast. One engineering team running Claude Code in automated CI/CD loops can drain a monthly budget in days. The CFO problem is now the bottleneck for AI adoption at the enterprise level. The technology works. The productivity gains are real. Uber's own data says 75% of AI code review comments are marked helpful by engineers. The constraint is that traditional annual budgeting was designed for tools with predictable per-seat costs, and AI coding agents have usage curves that look like cloud compute bills from 2015: exponential until someone notices. Every enterprise CTO is about to have the same meeting Praveen just had. The tools are too good to pull back. The costs are too unpredictable to ignore. And the companies that figure out token cost optimization first will have a structural advantage over every competitor still running annual budget cycles against exponential adoption curves.

I'm tempted to finally churn off Slack. We're paying ~$6k/year for 40 people and they just quoted me $21k/year for the business version that includes a BAA (and all the shitty AI features). Incredibly overrated software