Professional services engineer asked if a legacy API was still supported—I fed the question to Claude Code with my brainlift and code map, and it surfaced the deprecation analysis plus a step-by-step migration guide in 20 seconds. AI doesn't replace expertise; it scales it. #AI

RIP @windsurf 💀 After the latest planning mode changes, it’s basically dead. It ignores instructions, rewrites code I didn’t ask for, and produces gibberish. What used to be great is now unusable. By contrast, Claude Code delivered: I used continuous work across several days,

Does anyone know how to disable planning mode from @windsurf ? It is on by default now and causing some pain.

The takeaway: LLMs aren’t oracles — they’re echo chambers with compression. If you want bias, fine. If you want contrarianism, prime them with counter-narratives or antibias constraints. Next time you prompt for strategy: * Decide if you want consensus or disruption * Prime with

Same thing happened with other SPOVs Claude repeated: “Enterprise AdTech should consolidate services rather than embrace microservices.” “Hybrid OLTP/OLAP is superior to cloud-native data lakes.” These aren’t bugs — they’re mirrors. If you don’t define a new direction in your

Claude might be choosing to reflect a reality: a lot of enterprise blogs, whitepapers, and conference talks still position on-prem as: *Lower latency *More control over compliance *Vendor lock-in mitigation *Strategic autonomy in geopolitics If you’re designing greenfield

I’ve been testing Claude Code to extract for spiky points of view (SPOVs) on a product that use a data center. I let it search the web, wikis, and code. Every run, it keeps spitting out: “On-Premise Deployment is a Strategic Advantage, Not Legacy Technical Debt.” Is this a

Your LLM is your new RCA weapon—no extra tools needed: 1️⃣ Tech debt: Prompt your LLM to analyze diffs & flag risky legacy code 2️⃣ Signal debt: Feed logs & let the model surface missing alerts 3️⃣ Process debt: Chain-of-thought prompts route incidents to the right stakeholder Cut

Stop dancing around failures. A killer RCA digs into 3 debts: 1⃣ Tech debt that broke the tool 2⃣ Signal debt—alarm was there, we didn’t hear it 3⃣ Process debt—wrong person, wrong time Dig deep, fix these, and banish repeat SEVs for good. 🚀 #RCA #DevOps #IncidentMgmt

Teaching an AI to replace myself has been far tougher than I imagined—crafting a robust “brainlift” is no small feat. Have you tried building AI to take over your own role? I’d love to compare notes. #AI #ProductDefense #CTOthread

CEOs and CPOs can converse with the Assistant via @ephor's MCP interface to understand the rationale behind every recommendation—and debate priorities just as they would with me. That transparency is critical when AI steps into a CTO’s shoes.

The goal? To continuously ingest data from BrainLifts, support tickets, RCAs, compliance & security reviews—and our live code repositories—then run specialized agents to generate actionable defense plans before customers even request them.

As CTO, I’m charting our top product priorities—and defining our Product Defense Plan: proactive strategies to safeguard product health before issues ever surface. To operationalize this, I’m building an AI-driven Assistant with direct access to our codebase and data streams

After a long discussion, we landed a first version of Elicitation to the MCP draft specification. Lots more to work on and to evolve. Take a look

New course to bring you up to state-of-the-art at using AI to help you code: Build Apps with Windsurf's AI Coding Agents, built in partnership with WIndsurf (@codeiumdev) and taught by @_anshulr! AI-assisted IDEs (Integrated Development Environments) make developers’ workflows

That's cool. Things are moving really fast.

Tool of choice? @ephor It filters your feeds, refines your POV, builds your LLM context. Ephor makes your BrainLift actionable. In a world of average AI, your mind is the edge. 📈 Build your BrainLift. 🔥 Create new knowledge. 🧠 Train AI to follow your lead.

Webb’s DOK levels are your ladder: * DOK1: Recall facts * DOK2: Apply ideas * DOK3: Generate insights * DOK4: Create new knowledge across domains BrainLifts climb from DOK1 → DOK4

What’s a BrainLift? It’s your personal expert system: * Curated sources * Summarized insights * Spiky POVs that LLMs disagree with It trains AI to operate in your world