hacking.postgres.tv
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postgres=# select * from sessions where topic = 'ai-assisted-hacking';

#AI-assisted hacking

5 related sessions.

· 77:12 · youtube ↗

Agent hacking Postgres

Agent-assisted patch work around the wait-event timing submission.

The group reviewed Kirk Wolak's pg_dump patch for keeping loadable placeholders when table data is excluded, grounding the discussion in his large-table restore workflow. They debated a positive interface, filter-file actions, arbitrary dump queries, PII transformation, and referential-integrity risks, then posted supportive review feedback to pgsql-hackers. The final segment examined Salma El-Sayed's B-tree leaf-page merge design, including merged-page markers, scan correctness, vacuum cleanup, and review plans.

[timecodes · 8]
  1. Postgres 19 development opens and patches await review
  2. Kirk introduces the pg_dump placeholder patch
  3. Large-table dump and one-command restore use case
  4. Reviewing the option name and user interface
  5. Using AI to review design and mailing-list history
  6. Parallel chunks for restoring one large table
  7. Custom dump queries, filtering, and PII transformation
  8. B-tree leaf-page merge design and scan safety
#wait events#B-tree#AI-assisted hacking#hacking process@Nikolay Samokhvalov@Andrey Borodin@Kirk Wolak
-hackersCF #6984
active

correlated mapping
· 78:11 · youtube ↗

Agentic Hacking Postgres

End-to-end tests for archive-fed logical decoding and pause/resume behavior.

The session refined logical decoding from an archive-fed physical standby as a recoverable, production-independent pipeline: after losing the decoding node, a consumer can restore another standby at the acknowledged LSN and tolerate overlap. They reviewed the three-patch implementation and TAP test, found registration and naming issues, debated lock structure, and judged the code ready for discussion after fixes. They then specified an end-to-end WAL-G test with catalog churn, paused consumption, catch-up, and a final marker.

[timecodes · 8]
  1. Recoverable decoding after a standby is lost
  2. Archive-fed WAL decoding without touching production
  3. Naming the feature: logical decoding from archive
  4. Reviewing the three-patch implementation
  5. TAP test registration and test readability
  6. Reviewing pause-on-conflict code and locking
  7. Patch readiness and concrete submission fixes
  8. Designing an end-to-end WAL-G recovery test
#logical decoding#recovery#WAL#AI-assisted hacking@Nikolay Samokhvalov@Kirk Wolak
test design #43
active

direct mapping
· 72:37 · youtube ↗

AI or not AI; GSoC 2026; improving pglz compression

Evaluate agentic hacking, develop GSoC project ideas, and experiment with pglz compression.

The first half examined AI-assisted Postgres development: community overload, specification-first agent workflows, independent review, and personal responsibility for generated work. The second half audited an agent-produced pglz optimization series. Existing benchmarks mixed runtime and work done, while some optimizations changed compressed output. The group therefore narrowed the project to byte-compatible changes, required old-versus-new output tests, fixed-transaction-count and multi-platform benchmarks, and a small reproducible pgsql-hackers result; a reported 14% workload gain still needed verification.

[timecodes · 8]
  1. AI risks for the Postgres community
  2. Specification-first autonomous agent workflows
  3. Quality, review, and ownership of AI output
  4. AI policy for Google Summer of Code
  5. Reviewing the pglz optimization project
  6. Why the benchmark methodology was misleading
  7. Compression correctness and corruption tests
  8. Byte-compatible scope and revised benchmark plan
#compression#AI-assisted hacking@Nikolay Samokhvalov@Andrey Borodin@Kirk Wolak
pglz experimentGSoC ideaswait coveragepgss scalabilityB-tree merge
exploration

direct mapping
· 87:51 · youtube ↗

How to create Postgres patches with AI?

AI-assisted patch discovery, implementation, review, and submission.

The session developed a responsible AI-assisted patch workflow: treat prompts as engineering specifications, assign independent security, documentation, and testing reviewers, distrust praise, and use agents to summarize long CommitFest threads without surrendering judgment. They then applied that workflow to a patch that logs the LSN of DROP TABLE, enabling precise PITR after accidental deletion. The agent retrieved and rebased the patch, planned transaction, rollback, savepoint, and documentation tests, and continued adapting it to changed GUC infrastructure; final review remained pending.

[timecodes · 8]
  1. What AI changes in Postgres hacking
  2. Specifications and independent reviewer roles
  3. Maintenance work and critical AI feedback
  4. AI-assisted patch and CommitFest review
  5. Advice for learning Postgres development
  6. GSoC as an entry into core hacking
  7. Starting a live DROP TABLE logging review
  8. PITR use case, tests, and patch rebase
#AI-assisted hacking#hacking process@Nikolay Samokhvalov
tools PR #10
exploration

direct mapping
· 73:44 · youtube ↗

Vibe Hacking Postgres

Prototype merging sparse B-tree leaf pages and audit its correctness failures.

The workshop focused on a prototype for reclaiming B-tree bloat by merging adjacent sparse leaf pages. Kirk proposed an incremental, access-exclusive-lock design that first merges only one pair, prioritizing correctness of forward and backward scans. The pgindex_reclaim extension identified merge candidates, but execution crashed. Inspection showed incomplete parent-page handling and incorrect WAL/critical-section logic. The group chose to stop trusting the generated merge code, add a reproducible regression test, study related upstream page-deletion work, and restart from the smallest verifiable merge.

[timecodes · 8]
  1. Why merge sparse B-tree pages
  2. Forward and backward scan constraints
  3. Smallest verifiable merge design
  4. How the approach differs from pg_squeeze
  5. Building and running pgindex_reclaim
  6. Candidate pages found, execution crashes
  7. Critical sections, WAL, and parent updates
  8. Regression test and restart plan
#B-tree#AI-assisted hacking@Nikolay Samokhvalov@Andrey Borodin@Kirk Wolak
no public artifact mapped
exploration

direct mapping