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The AI Skills No One Is Teaching Product Managers (But Should Be)
You have the tools -- Claude Code and GPT-5.3 -- but here's the skill layer that makes them actually work.
Feb 21
•
Nilesh Barla
177
Investor And Venture Outlook On AI | Takeaways For Founders And Product Leaders
A grounded lens on where AI value will compound, which risks matter, and why execution discipline beats hype.
Feb 18
•
Arsh Shah Dilbagi
25
1
Claude Opus 4.6 vs GPT-5.3 Codex: Which AI Coding Model Should You Use?
A practical comparison for real PRs; when to use Claude for building and Codex for review, refactors, and reliability.
Feb 14
•
Nilesh Barla
113
2
Shipping Fast And Iterating At AI-Speed | Takeaways For Founders And Product Leaders
Ship fast in AI by learning faster: define “good,” dogfood, stay close to users, and prevent regressions with evals.
Feb 11
•
Arsh Shah Dilbagi
86
1
OpenClaw Is Not Magic; It's Just Good Architecture
Why event-driven design and persistent state create the illusion of an intelligent assistant.
Feb 7
•
Nilesh Barla
38
1
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Growth And Retention In An AI-first World | Takeaways For Founders And Product Leaders
Feb 4
•
Arsh Shah Dilbagi
226
1
Prompt Engineering as Product Strategy
Dec 13, 2025
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Nilesh Barla
61
Building Production-Ready Agentic RAG Systems
Dec 6, 2025
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Nilesh Barla
104
2
Claude Opus 4.6 vs GPT-5.3 Codex: Which AI Coding Model Should You Use?
Feb 14
•
Nilesh Barla
113
2
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Growth And Retention In An AI-first World | Takeaways For Founders And Product Leaders
AI makes products feel magical at first, but only trust, habit, and problem frequency turn novelty into durable retention.
Feb 4
•
Arsh Shah Dilbagi
226
1
When Everyone Can Build: Redesigning Product Work for the AI Era in 2026
AI is turning “who does what” into a moving target, so the winning teams will redesign roles, workflows, and accountability around outcomes, not titles.
Jan 31
•
Nilesh Barla
54
2
Building AI Products, Not Prototypes | Takeaways For Founders and Product Leaders
A production-first guide to opinionated workflows, environmental control, and evals that keep AI features reliable.
Jan 28
•
Arsh Shah Dilbagi
129
2
How to Ship Reliably With Claude Code When Your Engineers Are AI Agents
A PM-friendly playbook for plan-first agentic development using subagents, guardrails, and multi-model review to turn tickets into safe pull requests.
Jan 24
•
Nilesh Barla
73
2
Claude Code vs OpenAI Codex: Choosing Autonomous Agents for Production Velocity
Why Claude Code and Codex both exceed human parity—and why that's not enough.
Jan 17
•
Nilesh Barla
41
1
1
The AI Research Landscape in 2026: From Agentic AI to Embodiment
How agentic workflows, continual learning, world models, and architectural innovation will be reshaping AI from research breakthrough to production…
Jan 10
•
Nilesh Barla
17
1
3
Observability vs Monitoring for Agentic AI Products
Exposing AI agent decision failures and optimizing autonomous behavior through causal observability patterns.
Dec 27, 2025
•
Nilesh Barla
20
1
The MCP Product Playbook: From Idea to Prototype in One Conversation
How product leaders can build AI-powered applications in hours using model context protocol without writing code.
Dec 20, 2025
•
Nilesh Barla
27
Prompt Engineering as Product Strategy
Why your AI product's success lives in the system prompt.
Dec 13, 2025
•
Nilesh Barla
61
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Adaline Labs
The newsletter that swaps stale buzzwords for actionable insights. Our research-backed articles, expert commentary, and bold experiments with LLMs serve one purpose: to spark inventive thinking. By Adaline(.ai).
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