Enterprise Tech Leadership Summit Las Vegas 2024
2024-08-20..2024-08-22
Las Vegas, United States
who it's for
engineering leaders, engineering managers, senior software engineers, developer productivity engineers, platform engineers, CTOs
topics
AI-first developer tooling; 100-500 ms build targets; generative code assistants; code search with generative layer; copilot workspace to PR flow; automated provenance and testing pipelines; rapid reprioritization and job fairs; long-lived team ownership; scaling engineering headcount; history of interactive programming interfaces
| title | author | length |
|---|---|---|
| Interview: Sourcegraph Founder/CEO Slack Quinn | Gergely Orosz | 01m |
Argues that AI will upend developer tooling so logging, issue trackers, deployment and security scanners shift from human UIs to AI-first tooling that streams… | ||
| Interview: Sourcegraph Founder/CEO Slack Quinn | Gergely Orosz | 02m |
Sourcegraph recounts that several projects started in 2021 were reasonable but no longer align with top company priorities and get cut; teams built… | ||
| Interview: Sourcegraph Founder/CEO Slack Quinn | Gergely Orosz | 01m |
Sourcegraph keeps the original code search product for 11 years and layers a generative assistant called Cody on top, claiming it takes five years to land an… | ||
| Interview: Sourcegraph Founder/CEO Slack Quinn | Gergely Orosz | 02m |
Founder/CEO Slack Quinn says Sourcegraph learns from regrets 2021 product launches where features shipped that shouldn’t have, and takes responsibility for… | ||
| Interview: Sourcegraph Founder/CEO Slack Quinn | Gergely Orosz | 02m |
Sourcegraph reports growth from about 25 people in 2019 to ~180 now, claims software engineers transition naturally into CEO roles, and credits advisers and… | ||
| Interview: Sourcegraph Founder/CEO Slack Quinn | Gergely Orosz | 02m |
Company recounts several projects from 2021 that were plausible but not aligned with top priorities and would not be greenlit today, yet had users and teams… | ||
| Interview: Sourcegraph Founder/CEO Slack Quinn | Gergely Orosz | 02m |
Company headcount grows from 25 to 180 between 2019 and 2024 and the claim is that software engineers transition into CEO roles regularly, with computer… | ||
| Interview: Sourcegraph Founder/CEO Slack Quinn | Gergely Orosz | 01m |
Engineers who master AI coding assistants and code search tools like Sourcegraph see their market value jump, doing engineers become quasi-PMs/EMs work without… | ||
| Interview: Sourcegraph Founder/CEO Slack Quinn | Gergely Orosz | 02m |
Company uses a monthly job fair to reassign people to the highest priority work and spins up a cross-functional effort to build Cody. The experiment runs about… | ||
| Idan Gazit, GitHub, ETLS Vegas (22) | Idan Gazit | 03m |
GitHub Copilot workspace inspects a real repo, generates a concrete spec and pinpoints three files to change, then produces an editable PR that boots an… | ||
| Idan Gazit, GitHub, ETLS Vegas (01) | Idan Gazit | 02m |
Claims that the transition from 80-column punch cards to teletypes and then CRT terminals is the key shift from batch coding to interactive programming, backed… | ||
| Idan Gazit, GitHub, ETLS Vegas (07) | Idan Gazit | 01m |
A GitHub prototyping team builds and ships developer tools that leave the lab, starting with the original GitHub Copilot and continuing into more AI-driven… | ||
| Idan Gazit, GitHub, ETLS Vegas (32) | Idan Gazit | 01m |
Argues that AI enables in-place bidirectional editing so edits in code, natural language, or diagrams immediately mirror across representations, turning… | ||
| Idan Gazit, GitHub, ETLS Vegas (10) | Idan Gazit | 06m |
Compares ghost text (inline, forgettable suggestions) and chat (out-of-editor discussion) and argues both hit a ceiling for producing large multi-file code… | ||
| Idan Gazit, GitHub, ETLS Vegas (07) | Idan Gazit | 01m |
A GitHub prototyping group builds end-to-end developer tools and already shipped the original GitHub Copilot as proof it can move ideas into daily use; the… | ||
| Idan Gazit, GitHub, ETLS Vegas (34) | Idan Gazit | 01m |
Describes the shift from many narrow systems to a single generalized LLM that makes ML usable by anyone who can write English, then the reverse trend: a… | ||
| Idan Gazit, GitHub, ETLS Vegas (28) | Idan Gazit | 01m |
Claims that an English spec can compile into a working app using a prototype called speckling, and demonstrates a Hacker News reader app that runs on mobile… | ||
| Idan Gazit, GitHub, ETLS Vegas (04) | Idan Gazit | 02m |
Argues that AI for coding sits at an inflection point and most early work simply glues a bolted-on chat to existing tools, which underuses the medium. Traces… | ||
| Idan Gazit, GitHub, ETLS Vegas (29) | Idan Gazit | 01m |
Argues that adding an AI layer to the existing compile-and-build stack is inevitable but risky because compilers are deterministic and AI is not, so teams must… | ||
| Steve Yegge, Sourcegraph, ETLS Vegas (00) | Steve Yegge | 03m |
Argues that generative AI measurably amplifies senior engineers’ impact while reducing onramps for juniors, supported by hands‑on work building the Cody coding… | ||
| Steve Yegge, Sourcegraph, ETLS Vegas (99) | Steve Yegge | 03m |
Claims that zero interest rate policy plus a $2 trillion stimulus create a hiring boom starting March 2020, peaking around ChatGPT’s release, then reversing… | ||
| Steve Yegge, Sourcegraph, ETLS Vegas (25) | Steve Yegge | 02m |
Companies cluster at extremes: some already run 5 to 10 year GenAI programs while others have postponed evaluation and risk obsolescence. Adoption path is… | ||
| Steve Yegge, Sourcegraph, ETLS Vegas (10) | Steve Yegge | 01m |
Claim: measuring token counts and AI percentage of code is outdated and completions are a gimmick, so throw away metrics like acceptance rates and token… | ||
| Steve Yegge, Sourcegraph, ETLS Vegas (09) | Steve Yegge | 03m |
Claims that within 18–24 months all code is written by LLMs, backed by research co-authored with Jean, arguing industry pilots already use LLMs to do low-level… | ||
| Steve Yegge, Sourcegraph, ETLS Vegas (21) | Steve Yegge | 02m |
Claims that LLM-based coding assistants and an iterative “chop” workflow make developers 5–10x faster by generating code and then digging back into the… | ||
| Steve Yegge, Sourcegraph, ETLS Vegas (29) | Steve Yegge | 01m |
If ingesting 50 petabytes a day a single LLM context window is useless so an intelligent indexing layer is mandatory, producing search indexes, knowledge… | ||
| Paige Bailey, ETLS Vegas (99) | Paige Bailey | 01m |
Gemini ingests recorded user sessions and automatically produces detailed friction logs with timestamps, quoted user actions, and classified error types, then… | ||
| Paige Bailey, ETLS Vegas (23) | Paige Bailey | 03m |
A PRD feeds into Gemini which decomposes PRD into subtasks and creates a ticket per subtask, then assigns an agent or person and loops until the software… | ||
| Paige Bailey, ETLS Vegas (00) | Paige Bailey | 01m |
Generative AI is changing how products are built at Google by moving large research models out of internal sandboxes and into real user surfaces and developer… | ||
| Paige Bailey, ETLS Vegas (06b) | Paige Bailey | 01m |
Demonstrates that Gemini processes recorded user sessions and generate the detailed friction log from raw video, timestamps where users struggle, and produces… | ||
| Paige Bailey, ETLS Vegas (06) | Paige Bailey | 09m |
Google describes a code AI suite built on over a trillion tokens and 500,000 aggregate years of engineering telemetry and 80 million code review edits powering… | ||
| Paige Bailey, ETLS Vegas (20) | Paige Bailey | 02m |
Describes using a super large context window model to ingest and cluster feedback from tens of thousands to hundreds of thousands of forum posts GitHub issues… | ||
| Paige Bailey, ETLS Vegas (05) | Paige Bailey | 01m |
Google describes a small, cheap, fast LLM that powers billions of users and claims it creates a new quadrant of model performance by trading size for latency… | ||
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