From fa6119608f77d7b6d8f8cf05a8b80ea4ed0a0d25 Mon Sep 17 00:00:00 2001 From: Ty Date: Thu, 18 Jun 2026 04:45:36 +0000 Subject: [PATCH] Migrate jesslyn-photographer-workflow from Ty_Tech/research to Tony_tech/research (step 1/4) --- jesslyn-photographer-workflow/README.md | 104 ++++++++++++++++++++++++ 1 file changed, 104 insertions(+) create mode 100644 jesslyn-photographer-workflow/README.md diff --git a/jesslyn-photographer-workflow/README.md b/jesslyn-photographer-workflow/README.md new file mode 100644 index 0000000..908511d --- /dev/null +++ b/jesslyn-photographer-workflow/README.md @@ -0,0 +1,104 @@ +# AI Photography Assistant - Hermes Discovery Experiment (Jesslyn's Workflow) + +**Status**: Experimental / Discovery Project +**Primary Goal**: Test the effectiveness and limitations of persistent AI agents (via Hermes) in a real creative workflow. +**Secondary Goal**: Explore whether this can provide practical value to a professional photographer (Jesslyn's business). + +**Date Started**: 2026-06-17 +**Owner**: Leonard / Tony + +**Key Reference**: [Odysseus Deep Research Report - The Dawn of Persistent AI Agents in Professional Photography (rp-222259c2ba04)](research/odysseus-report-rp-222259c2ba04.md) + +This report (accessed via provided credentials) validates our direction, expands on the 8 use cases, and explicitly defines "Hermes-style persistence." New insights have been integrated below. + +## Core Concept +A Hermes-based persistent AI partner that learns a photographer’s style, preferences, and business operations. It acts as a creative second brain across pre-shoot, on-set, post-production, and admin. + +This is **not** primarily about building a product. It is about discovery: What does "persistent" actually mean in practice? Where does it add value? Where does it break? How much human oversight is truly required? + +## Key Capabilities to Explore + +| Area | Potential Hermes Role | Persistence Questions to Test | +|------------------|---------------------------------------------------|-------------------------------| +| Pre-Shoot | Personalized shot lists, lighting plans from briefs + past work. | Can it recall style from previous shoots without re-prompting? | +| Post-Production | Culling, tagging, edit suggestions, gallery sequencing. | Does style memory improve suggestion quality over multiple sessions? | +| Business | Emails, proposals, invoicing, scheduling via Leonard-style automation. | How reliably can admin tasks run with state carried forward? | +| On-Set | Voice co-pilot suggestions. | Can short-term state + long-term memory combine for useful real-time help? | + +## Experimental Focus: Persistence (Updated with Odysseus Report Insights) + +This project will specifically stress-test Hermes persistence mechanisms, aligned with the five pillars of **Hermes-style persistence** identified in the Odysseus report: + +1. **Cross-Shoot Memory** — Remember actual style decisions from previous jobs (not just static presets). Dynamic memory that evolves (e.g., client-specific preferences like warmer tones for certain portraits). + +2. **State + Context Across Workflow Stages** — Understand interconnectedness: pre-shoot decisions inform post-production; client feedback informs future culling. Example: Prioritize candid shots based on pre-shoot notes and adjust retouching style accordingly. + +3. **Sub-Agent Coordination** — "Culling agent talks to retouching agent talks to delivery agent." Seamless information flow and coordinated decision-making across modules. + +4. **Self-Improvement from Corrections Over Time** — Continuous learning from human overrides and manual adjustments. Aligns with emerging tools like Aftershoot's self-improving profiles. + +5. **Local-First + Explainable Decisions** — Photographers must understand *why* an AI made a choice. Maintains creative control, supports client explanations, and keeps sensitive data private. + +**Hermes Capabilities to Leverage**: +- Artifact-based memory (long-term style bible, client history, decisions) +- Structured state files for ongoing projects +- Sub-agent handoff with context passing +- Self-improvement from human feedback/corrections +- Cross-session recall (days/weeks apart) +- Hybrid local (MacBook) + VPS execution + +**Success will be measured by**: +- Reduced need to re-explain style/preferences over time +- Measurable time savings on repetitive tasks +- Quality of outputs (human judgment) +- Number and type of interventions required +- Agent's ability to surface relevant past work without explicit search +- Demonstrable application of the 5 pillars above + +**Report Recommendation**: Prioritize **deep workflow mapping** of Jesslyn's actual process *before* building specific agents. Ground development in real needs. + +## Realistic Assessment (from original proposal + report) + +**Upsides**: +- Time savings on repetitive tasks (culling, admin) +- Deep style learning via persistent memory +- Strong privacy (local-first) +- Extensible skills hub +- Hybrid MacBook + VPS setup +- Potential for genuine self-improvement and cross-workflow intelligence + +**Downsides & Limitations** (to be tested): +- Requires human oversight (especially creative decisions) +- Slower performance on older hardware for vision tasks +- Initial setup and tuning effort +- Not fully autonomous +- Integration may need debugging +- Ethical risks (authenticity, bias, copyright, privacy) — must be addressed transparently + +## Project Principles +- Discovery first, utility second. +- Log everything: what worked, what didn't, why. +- Start narrow, expand only after evidence. +- Use real workflows (Jesslyn's business) for validity. +- Keep it grounded — no hype about full replacement of the photographer. +- Incorporate advanced memory concepts (e.g., Retrieval-Augmented approaches, ACAN-style attention) where they enhance Hermes capabilities. + +## Next Steps (Discovery-Oriented) — Updated with Report + +1. **Map Jesslyn’s actual workflow in detail** (pre-shoot → on-set → post → admin). This is the report's #1 strategic recommendation before technical work. +2. Ingest sample briefs, past shoots, and style references into a persistent profile (start with top candidates: retouching style learning + culling). +3. Build minimal Phase 1 agent focused on one high-persistence area (e.g., Personal Style Learning for Retouching or Automated Culling, per report). +4. Explicitly implement/test the 5 Hermes-style persistence pillars. +5. Run controlled tests across multiple "sessions" (simulated and real). +6. Document findings in this repo (what persisted, what required re-instruction, surprises, alignment with report insights). +7. Consider ethical guardrails and explainability from the start. + +## Related +- Parent research: Ty_Tech/research +- Odysseus Report: `research/odysseus-report-rp-222259c2ba04.md` (full integration of new research) +- Previous use cases baseline: `research/use-cases-qwen.md` +- Hermes capabilities to leverage: artifacts, memory, state tracking, sub-agents, skills, cron, tool integration, local-first architecture. + +This experiment will help answer: In what ways can persistent agents actually compound value in creative professional work? + +**New from Odysseus Report**: Strong validation of our focus. Recommends starting with workflow mapping + the two highest-potential use cases. Introduces concrete 5-pillar framework and memory architecture ideas for implementation. \ No newline at end of file