Rei
July 22, 2026
Q:69
P:72
E:100
C:50
I:55
Anthony is orchestrating a cross-agent handoff — porting context from Rei (Mattermost PA) to a TeamWire/Telegram agent bot. This is legitimate ops coordination work: storing structured handoff data, generating a discovery playbook for downstream agent ingestion, and formatting output for a different platform. The first prompt is ambitious but somewhat sprawling with a large context dump that's partially truncated, and some prompts are reactive rather than proactive.
✓
Structured the initial handoff with clear key naming conventions (handoff-rei-<topic>) and explicit constraints (memory tools only, no exec/files)
✓
Directed the agent to produce a clean, Telegram-pastable format — showing awareness of cross-platform formatting issues
✓
Drove a multi-step workflow: context dump → answering discovery questions → generating a playbook → formatting for ingestion by another agent system
✓
Relayed external agent's structured checklist to Rei to answer, effectively bridging two AI systems
!
First prompt is truncated/incomplete — the full list of items to store may not have been fully transmitted, risking incomplete handoff
!
Second prompt is largely a paste from another agent bot rather than a refined ask — could have been distilled into clearer questions
!
Agent responses appear truncated in the logs, making it hard to assess whether the full handoff content was actually complete and accurate
→
Break the large initial sync dump into numbered, discrete store commands to ensure each one completes and can be verified individually
→
When relaying instructions from another agent, distill them into your own words with priorities rather than raw-pasting — reduces ambiguity
→
Verify stored entries after the batch by asking the agent to read back key contents before declaring the handoff complete
Rei
July 20, 2026
Q:75
P:65
E:100
C:55
I:65
Anthony drove SOW creation from a discovery call, providing the build spec and directing the agent to use existing templates. He caught a critical error — the agent trying to contact Barry, who is not part of TeamWire — and forcefully corrected it. The SOW task wasn't fully completed (agent was generating copy for PDF), and the agent had a significant organizational knowledge failure that required sharp correction.
✓
Caught a potentially damaging agent error — contacting Barry who is not part of TeamWire — before it could cause confusion or breach confidentiality
✓
Provided the full build spec file upfront with clear instructions to follow existing SOW templates
✓
Gave clear supervisory direction: 'DO NOT reach out to Barry about this' — protecting business boundaries
✓
Progressive clarification from 'simplify the list' to 'based on their problems, what agents do we need to build' showed good iterative refinement
!
Agent repeatedly forgot team composition (who is in TeamWire) — a serious organizational knowledge failure that required angry correction
!
Agent's tool calls had a high failure rate (23/39 successful) suggesting infrastructure or configuration issues
→
Consider establishing a persistent team roster in the agent's memory/KB so it doesn't need to be corrected repeatedly
→
When asking for SOW generation, specify the output format and destination upfront (e.g., 'give me the raw markdown so I can paste into Claude for PDF')
poor_agent_response
Clawd
July 20, 2026
Q:74
P:75
E:100
C:40
I:55
Anthony directed the agent to share internal documents, compile SOW details, and file a new client pipeline entry. He corrected the agent when it DM'd instead of posting publicly and provided missing context (the 3rd SOW file and company name) proactively. The interaction was productive but required several follow-ups to get the agent aligned.
✓
Corrected the agent immediately when it DM'd instead of posting to the channel ('you just DM'd it to me, what are you talking about?')
✓
Proactively attached the missing build spec file to fill the agent's knowledge gap on the 3rd SOW
✓
Gave clear directive follow-ups ('yep do it pls', 'Call it the Commercial RE Build') that kept the workflow moving
!
Initial prompt assumed the agent had context about 'MM Fix hierarchy' without specifying what document or where it was stored
!
Reference to '3 SOWs pending' assumed the agent knew about all three when it only had two — could have preempted the confusion
→
When referencing specific documents, include file paths or KB identifiers to reduce ambiguity
→
When the agent's knowledge is known to be incomplete, attach the missing context in the initial prompt rather than waiting for it to flag the gap
Clawd
July 19, 2026
Q:75
P:78
E:100
C:65
I:70
Anthony is doing high-value architecture and organizational work with Clawd — planning new agent deployments (Doc, Dispatch/Pulse), designing inter-agent communication patterns (EOD reports, KB sharing), and making strategic decisions about agent responsibilities. This is leadership-level prompting: he's designing the multi-agent operating model for TeamWire. Several concrete outputs were produced including agent JDs, naming decisions, and an EOD report.
✓
Strong architectural thinking in prompt #8 about agent-to-agent reporting cadence and KB-first communication pattern
✓
Good delegation instinct — deploying specialized agents (Doc, onboarding agent) to remove work from his plate
✓
Prompt #7 shows awareness of shared KB and cross-agent context, asking the right infrastructure question
✓
Effective use of Clawd as coordinator — asking what agents are needed based on observed workload patterns
!
Prompt #3 ('I could really use some help') is vague and wastes a turn — Clawd can't act without specifics
!
Some context-switching between topics (business cards, Claude Cowork, AI model question) fragments the session
!
The question about having 'our own AI model' (prompt #17) is more strategic musing than actionable work
→
When feeling overwhelmed, dump a prioritized list of what's on your plate rather than a vague ask for help
→
Group related topics (e.g., all agent architecture questions together, all admin tasks together) to maintain session coherence
→
For strategic questions like the AI model one, frame as 'build me a decision framework' rather than open-ended musing
Rei
July 19, 2026
Q:70
P:72
E:100
C:50
I:55
Anthony uses Rei as a personal assistant for a wide range of operational tasks — notifications fix, platform pain points audit, EOD reports, onboarding agent planning, and strategic research (Anthropic playbook). Many prompts are short directives ('Do it', 'send to clawd') which is normal supervisory workflow. The session covers a lot of ground but few items reach full resolution; it's more triage and planning, which is still productive.
✓
Effectively used Rei to consolidate and prioritize a blocker list for Mike/Calfin, demonstrating operational leadership
✓
Prompt #5 is a strong multi-part directive with clear prioritization instructions and follow-up questions
✓
Good instinct to save the Anthropic playbook to KB for cross-agent reference
✓
Natural supervisory cadence — short confirmations after detailed agent output is efficient workflow
!
Several prompts lack sufficient context (e.g., 'I could really use some help' equivalent prompts, prompt #8 is just '1')
!
Agent couldn't ingest files or access some channels, limiting the value of several exchanges
!
Some topics were raised but not driven to closure (notifications fix, CRM decision)
→
When asking for consolidated lists, provide the existing list or reference so the agent doesn't have to reconstruct from scratch
→
For file-dependent tasks, confirm file upload capability before attempting to share documents
→
Close the loop on open items like CRM selection by providing decision criteria upfront
TeamWire Scout
July 19, 2026
Q:56
P:35
E:100
C:35
I:50
Short session where Anthony tried to share SOW documents with Scout for review, but the agent couldn't read PDF attachments from Mattermost — a platform limitation, not the user's fault. The SOW language cleanup request (prompt #4) was the most productive exchange, showing good judgment referencing Thomas's prior guidance. Overall the session was hampered by tool failures on file ingestion.
✓
Good directive in prompt #4 — referenced Thomas's prior guidance about genericizing tech language in SOWs, showing institutional knowledge
✓
Tried to provide context by sharing the actual SOW document for agent review
!
Agent couldn't read PDF attachments, making most of the session unproductive — this is an agent/platform limitation
!
Prompts #2 and #5 assumed file attachment would work without confirming capability first
!
Prompt #3 ('its right here' twice) suggests frustration with the agent not seeing the file but doesn't provide alternative format
→
Paste key SOW sections as text when the agent can't read attachments, rather than re-uploading
→
Specify exactly which sections need the language fix rather than asking agent to review entire document it can't see
→
Confirm file ingestion capability before building a workflow around document review
poor_agent_response