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How The Product Role Is Moving To Building And Verification
As AI speeds up execution, product leaders must focus more on product verification, evidence, judgment, and what is worth shipping.
Aug 8
•
Nilesh Barla
240
1
July 2026
Eval-First Product Design For Frontier AI Products
The evaluation suite is the specification your frontier product actually runs on. Everything else is intent.
Jul 31
•
Nilesh Barla
241
1
What Product Leaders Should Stop Doing Now That AI Can Do It
A practical framework for removing low-leverage work without outsourcing judgment.
Jul 25
•
Nilesh Barla
175
What Is An Agentic Stack, And Why Does It Matter More Than the Model?
A practical guide to the routing, context, tools, verification, and control layers that turn AI models into reliable agents.
Jul 18
•
Nilesh Barla
103
2
What Is Loop Engineering, and Who Owns It?
The role that shapes how AI agents halt, hold state, and recover, plus a maturity model to score your team against.
Jul 11
•
Nilesh Barla
128
Agent Replay Is A Product Surface, Not A Debugging Feature
Agent replay for production AI agents. The trace spec, who it serves, and why to build it in from day one.
Jul 4
•
Nilesh Barla
167
1
June 2026
The Long-Horizon AI Agents Ceiling Is A Product Problem
The planning ceiling is real, measurable, and not closing fast enough to be a roadmap. Five product moves that bypass it now, including the one that…
Jun 27
•
Nilesh Barla
111
1
The Self-Improving Agent Is A Production Pattern Now
Agentic harness engineering is the discipline that builds one. The five layers, what they decide, and why this is the pattern that wins production AI in…
Jun 20
•
Nilesh Barla
84
4
3
Chat Is the Wrong Default for AI Products
Chat works for exploration. For everything users do repeatedly, a button, a canvas, a delegated agent, or a background listener works better.
Jun 13
•
Nilesh Barla
109
1
Prompt Injection Is Not a Prompt Problem
The tool layer is where agents get compromised. Nobody has been looking at the right layer.
Jun 6
•
Nilesh Barla
212
1
May 2026
The Operating Loop: How Production AI Agents Actually Get Better, And Where The Loop Breaks
Three orphan disciplines — observability, evaluation, improvement — make one loop. The loop breaks at the seams.
May 30
•
Nilesh Barla
66
2
What Happens When Your AI Agent Interacts With Everything
A practitioner's framework for model selection when your agent's connectivity outgrows what benchmarks measure.
May 23
•
Nilesh Barla
156
2
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