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Lenny's Knowledge Sketch · GitHub Copilot

The Future of Software: AI Copilots & Developer Rethinking

Inbal S
Chief Product Officer, GitHub
FORMERLY: AWS, MICROSOFT
The Shift

Developers:
From Code Writing
to Systems Thinking

JUNIORSENIORWITHOUT AIWITH COPILOT
"Developers need to form a different thinking. You start figuring out how to use AI tools to be successful. It's no longer just code writing, it's evolving your thinking to the big picture, to connected systems."
  • Junior devs can spend time understanding systems from day one instead of learning syntax
  • Architecture and design thinking move earlier in developer careers
  • The human in the loop remains central, Copilot is a copilot, not a pilot
Impact by the Numbers

37K Organizations, 1.5M Developers, Measurable Gains

55%
faster code writing
85%
more confident in code quality
15%
faster code reviews
88%
less frustrated
  • 92% of developers already using AI tools, it's table stakes
  • Accenture: 88% of suggested code retained in production
  • Developers spend <25% of time actually writing code; rest on meetings, reviews, builds, legacy code
What's Most Underhyped

AI-driven testing: More code → more critical to test. Unit, integration, load, security, penetration testing all need AI-powered generation.

What's Overhyped

Replacement: AI won't replace humans. You need humans in the loop because AI cannot replace innovation, that creative spark that is the center of humanity.

The Mistakes Teams Make

How Companies Get AI Adoption Wrong

  • Expecting magic: "Here's a tool, go use it." Requires change management, not just tool deployment
  • AI for AI's sake: Asking "What should we do with AI?" instead of "What problem are we solving?"
  • Starting backwards: Plastering AI on things instead of identifying workflow friction first, then applying AI
  • Wrong metrics: Time is not quantifiable, you can write bad code fast. Focus on time-to-value instead
The Right Framework

Start with customer problem → identify where developers lack time (meetings, reviews, legacy code digging) → apply AI to automate manual/config-heavy tasks → measure time-to-value and developer happiness

Key Insight

Developers don't lose jobs. They shift to higher-value work: collaboration, innovation, architecture. That time gain = happier devs = better retention.

Metrics That Matter

Measuring Copilot Success

  • Not just time: Translate time → efficiency → productivity
  • Code quality: Can you improve security with Advanced Security tools?
  • Developer happiness: The ultimate metric, are devs more focused, less frustrated?
  • Time-to-value: From task assignment to realized value (revenue, adoption, market speed)
The TrapProductivity is not the right metric for every use case. For security tools, measure prevention (secrets leaked, bugs caught). For collaboration, measure cycle time. Combine metrics = developer happiness.
Contrarian Truths

What Inbal Gets Right About AI in Dev

✗AI replaces developersINSTEAD →✓ AI frees devs from toil. They do more creative, high-value work. Retention improves.
✗25% efficiency = 25% fewer peopleINSTEAD →✓ Dev time unlocked goes to collaboration, innovation, architecture. You need the humans more, not less.
✗More code = more productivityINSTEAD →✓ You can write bad code fast. Productivity = time-to-value + quality + developer happiness combined.
✗Copilot is a replacement toolINSTEAD →✓ Copilot is a collaboration and leverage tool. Devs pick and choose what to delegate, what to keep crafting.
Based on Inbal S's episode on Lenny's Podcast. All ideas on this page are from the episode.Watch on YouTube
GO DEEPER IN THE EPISODE
04:17 Why generative AI is not going to replace developers in the near future05:54 Why AI-driven testing is underhyped07:48 What the next 3 to 5 years will look like10:13 Stats around the use of GitHub Copilot12:07 How Copilot enables engineers to work more efficiently13:38 Common mistakes when adopting AI into your workflows16:42 How GitHub operationalizes “dogfooding”18:46 The philosophy behind Copilot20:24 Copilot’s success metrics24:54 How Copilot encourages collaboration26:37 What we lose when AI writes code for us29:35 A retrospective on the generative AI space30:47 Inbal’s thoughts on the future of AI32:35 How to make space for innovative product ideas34:37 How GitHub stays on the cutting edge of innovation36:44 The GitHub Next team39:20 Advice for early product managers42:17 Inbal’s “biggest learning” from her career45:34 Inbal’s closing thoughts46:19 Lightning round
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