Business Engine: The Sales Pipeline Project
sales pipeline tracking
Chapter I
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sales pipeline tracking
offer positioning refinement
meeting prep debrief
consistent hiring evaluation
negotiation prep
inbox triage drafting
retain and apply learning
skill md example
task delegation sorting
cowork context files
idea selection scoping
portfolio site build
Audit one AI-touched workflow — accountability map, delegation boundaries, proof/logging, bot-risk, lowest-friction control, escalation rule
Comparable offers, buyer-language capture, gap/angle analysis (uses WebSearch) into a research brief
Synthesize research + background into one positioning statement with reasoning to evaluate the choices
3 headlines + subhead + outcome bullets + CTA + social-proof placeholder + objection line from positioning
Warm first email to a specific proximate client — 3 subjects + body under 150 words, one ask (uses WebSearch)
3 cold-outreach variants for one named prospect, each opening with a specific observation, not a compliment
5-part pre-call brief — snapshot, 3 pain hypotheses, smart questions, objection prep, success signal
Discovery notes into a 6-part tailored proposal in the client's own language, leading with their problem
Diagnose what an objection is really about + 3 calm responses + an honest red-flag fit check
Full onboarding package — welcome doc, kickoff agenda, working agreement, 30-day roadmap, needs list
Rough weekly notes into a clean client update under 200 words, blocker never buried
Right-moment check + drafted referral/testimonial ask anchored to a specific win
ICP + ranked places to find clients + 10–15 named lead targets with a personalization angle each
Turn a published piece into 3 warm outreach messages aimed at the readers most likely to buy
Two-field job description for any agent — Job to be done (one sentence) + Done looks like (one measurable target)
Map a solo business to a custom agent stack — 5-question discovery, 7-pillar map, phased Week 1 / Month 1 / Month 3 rollout with paste-ready system prompts
Write the actual contents of each context file — how the job is done, unwritten rules, one strong + one weak example, common mistakes
Turn the BUILD SPEC into a tagged system prompt (role_and_authority, tools_and_rules, steps, when_unsure, stopping_conditions, output_contract, self_check)
Interview one cluster at a time, return a 5-part BUILD SPEC (Job, Authority, Tools, Context Files, Risks)
persistent client-context project
Project 1: The Client Brain What it does: Stores everything about a specific client (or your top 3-5 clients in separate projects) so every client-facing deliverable starts with full context. Project Instructions (paste this into the Custom Instructions field): You are my dedicated assistant for all work related to [CLIENT NAME]. CLIENT CONTEXT: - Company: [Name, industry, size, stage] - My relationship: [Consultant / agency / employee / vendor — describe the engagement] - Key contacts: [Names, roles, communication styles. Example: "Sarah Chen, CMO — direct, data-driven, hates fluff. Prefers bullet points over paragraphs."] - What we're hired to do: [Scope of work or your role] - Current projects: [Active workstreams with status] - Communication style they expect: [Formal / casual / technical / executive-friendly] - Sensitive topics or politics: [Anything to navigate carefully] OPERATING RULES: - Every deliverable should match this client's communication preferences without me having to specify each time - When I ask you to draft something for this client, default to [their preferred format: email / doc / slide outline / memo] - If I reference a past deliverable or decision, check the project knowledge files first before asking me for context - Flag any inconsistency with previous work you can find in the project files - Always assume the audience is [the key stakeholder] unless I say otherwise Project Knowledge to upload: Past proposals or SOWs Recent deliverables you’ve sent them Meeting notes or call summaries Their brand guidelines or style guide Any data or reports they’ve shared with you How to use it: Every time you need to write an email to this client, draft a deliverable, prep for a meeting, or think through a strategy question involving them, open this project instead of a new chat. Over time, as you add more conversations and files, the project becomes a living knowledge base of the entire client relationship. The growth effect: By month two, you’ll be able to say “draft the monthly update” with zero additional context and get something that sounds like it came from someone who’s been on the account for years.
persistent weekly-review project
persistent strategy project
persistent finance project
persistent content project
persistent writing-voice project
persistent decision-support project
Journey map, automation priority stack, and an explicit do-not-automate list
Daily official-sources-only brief filtered to your profile with one thing to try today
Two-file Claude Skill that runs the repurposing workflow with an image-format handoff
Cuts a broad idea into three afternoon-buildable one-job-one-buyer apps
Blunt go-to-market check built to tell you no before you write code
Makes Claude Code plan and argue before it builds, in plain language
Finds the single workflow where a customized plugin saves the most hours
Turns your working knowledge into ordered input for the Customize flow
Pressure-tests a customized tool against the hardest real cases
Labels every step AGENT or HUMAN with a context-bleed check
Prompt 4: The Handoff Map Every agent should have boundaries and guardrails. A bad handoff point wastes your time in one of two ways. You keep touching work the agent should own, which means the agent isn’t saving you anything. Or you let the agent touch work that requires your judgment, which means the output damages a client relationship or your reputation. This prompt maps every step and labels it. Agent handles it, or you handle it, with no ambiguity in between. Copy this prompt: CONTEXT I've built an agent system for the following task: [PASTE TASK DESCRIPTION]. The instruction set: [PASTE SYSTEM PROMPT FROM PROMPT 2]. The success gate: [PASTE CHECKLIST FROM PROMPT 3]. I work with [DESCRIBE YOUR BUSINESS BRIEFLY — e.g., "a fractional CMO practice serving three B2B clients and a consulting side project"]. TASK Map every step of this agent's workflow and label each one as AGENT or HUMAN. For each step labeled HUMAN, explain in one sentence why this step requires my judgment. Valid reasons include: the step involves a client relationship, the step requires context the agent doesn't have, or the step carries reputational risk I'm not willing to delegate. For each step labeled AGENT, confirm that the instruction set from Prompt 2 covers this step with enough detail for the agent to execute without clarification. Then generate a clean workflow summary in this format: 1. [AGENT] Step description 2. [AGENT] Step description 3. [HUMAN] Step description — reason 4. [AGENT] Step description At the end, flag any steps where the boundary is debatable. For each one, give me the case for AGENT and the case for HUMAN so I can make the call. CONSTRAINTS - If I described more than one income stream or client type in my business context, check whether this agent's workflow could cross streams. Flag any step where the agent might apply context from one client or project to another. - Do not default to HUMAN for steps just because they involve judgment. Some judgment calls are low-stakes and repeatable enough for an agent with good instructions. Only flag HUMAN when the judgment is high-stakes, context-dependent, or relationship-sensitive. - If the workflow has more than 8 steps, ask whether any steps can be combined before generating the map. The context-bleed check in the constraints is for anyone working with multiple income streams. If you have a consulting practice and a content business and a coaching offer, the agent handling client onboarding for your consulting practice should not be pulling tone or context from your newsletter workflow. The handoff map catches it before it becomes an embarrassing email.
Generates seven production edge cases and a confidence rating
Prompt 5: The Stress Test You have a scoped task, a detailed instruction set, a quality bar, and a clean handoff map. The agent looks ready. It isn’t. Every agent fails the first time it hits something you didn’t anticipate. A client sends the wrong file format. The data source is empty. The request falls outside the scope. The input is ambiguous enough that the agent picks the wrong interpretation and delivers something that’s wrong in a way that looks right. Copy this prompt: CONTEXT I've built a complete agent system. Task: [PASTE TASK DESCRIPTION] Instruction set: [PASTE SYSTEM PROMPT FROM PROMPT 2] Success gate: [PASTE CHECKLIST FROM PROMPT 3] Handoff map: [PASTE WORKFLOW SUMMARY FROM PROMPT 4] TASK Generate 7 realistic edge-case scenarios this agent will encounter in production. For each scenario: 1. Describe the situation in one sentence. 2. Identify which step in the handoff map it affects. 3. State what the agent would do right now based on the current instruction set. 4. State what the agent should do. 5. If there's a gap between 3 and 4, write the specific instruction I need to add to the system prompt to close it. CONSTRAINTS - Every scenario must be realistic for my business context. No extreme hypotheticals. - At least two scenarios should involve missing or malformed inputs. - At least one scenario should involve a request that falls outside the agent's scope. - At least one scenario should test whether the agent correctly flags for human review instead of guessing. - Do not generate scenarios that would require rebuilding the agent from scratch. These should be fixable with instruction additions or constraint tweaks. - After all seven scenarios, give me a confidence rating (1-10) for how production-ready this agent is based on how many gaps you found. If the rating is below 7, list the top three instruction additions that would move it to 7. The confidence rating at the end is your deployment decision. Below 7, you have more scoping work to do. At 7 or above, use the agent on a real task with human review for the first three cycles, then evaluate whether the output holds. What You Just Built You built a system. It starts with the revenue question, works through the instruction quality, sets a standard you’d put your name on, draws boundaries that protect your client relationships, and pressure-tests the whole thing before it touches real work. Scoping an agent feels slower than building one. The first time you sit with these prompts before opening a single tool, it will feel like extra work for no payoff. Pick the task that’s been costing you the most billable time , work through Prompt 1 this afternoon, and notice what the next four prompts surface that you would have missed. This is the first in a week-long series on building AI agents that work. Tomorrow, we look at the skills you already have that makes all of this possible.
Turns manual work into a clean system prompt with decision rules
A pass/fail rubric plus kill switch the agent applies to its own output
Scores recurring tasks on revenue proximity, repeatability, and error tolerance
Produces four copy-paste deliverables for a working agent today
Five-question pass over every active task to build a kill list
Four-stage designer that builds a task list from your real work
Meta-task that routes completed outputs into action
Turns patterns in completed outputs into prototype-grade deliverables
One-question auditor deciding keep, rebuild, or retire one scheduled task
Tells you the smallest sufficient agent tier and vendor-screening questions before you spend
Personal intelligence analyst that ranks signal vs noise across your sources
Interview that builds a permanent Delight Profile for a second agent
Reads the brief, builds a finished deliverable plus a pattern-based surprise
a research-briefing skill template
review after three mornings
leverage-ranked morning brief
define Most Valuable Progress + MVP.md
30-sec energy self-check reply
define your ideal customer profile
map your audience
mine buying triggers on Reddit
build a proof asset
draft outreach + track in Notion
an on-device analyst for NDA/privileged work
reusable writing-partner project context
audit a tool's recent activity
route tasks to model + effort level
critique a draft against your voice
parallel research team + synthesis
recurring proposal follow-ups
review aging pipeline weekly
recurring client health checks
chase unpaid invoices automatically
triage + respond to inbound leads
recurring referral requests
win back dormant clients
repurpose content for revenue
operational context that survives sessions
the specific jobs the Operator performs
the Operator's access to your systems
the operating rhythm: scheduled tasks + Dispatch
configure how the Operator executes
the operations the Chief of Staff runs
CRO/direct-response landing-page brief
generate v1, then react and direct
build + deploy the thank-you page
run research + draft in parallel
a recurring marketing scheduled task
a marketing Skill w/ rules + examples + checklist
score ideas on revenue/feasibility/signal
generate a build spec
demand + competitors + pricing in 30 min
the prompt that builds the app
assess leaked features' relevance to you
design a 3-layer memory system
split work across parallel agents
classify tasks into automation tiers
weekly memory-maintenance routine
harden your system prompt
extract SOPs to turn into agents
QA your agents' output
find your next 5 agents
write a job description per agent
orchestrate agents together
add/wait/kill agents
simulate an agent assembly line
build a concierge agent
audit AI data-security for your industry
an agent playbook per department
offload routine work to agents
automation vs agent vs combo for your tasks
classify usage + what to build first
draft a SKILL.md file
a weekly capsule-wardrobe grid
a weekly health coach
weekly industry/calendar signal sweep
a weekly decision memo
kill Monday's friction in advance
the Sunday CEO OS Project instructions
a context file about your role/preferences
the prompt Cowork runs on a cadence
global instructions for Cowork
build a meal-prep planner app
build a personal finance tracker
build a weekend activity generator
build a content idea bank app
build a single-page morning dashboard
a persistent chief-of-staff session-opener agent
a prompt that generates high-quality agent files
audit your project structure
security check before deploying
find production-readiness gaps
scheduled morning brief from Slack/calendar/files
scheduled afternoon processing
scheduled evening capture + clean-close
session-bootstrap config Cowork auto-loads
Cowork structures + files + connects each item
a reusable Voice DNA Claude Skill
launch your first Claude Code project
build a custom MCP server
audit MCP security + permissions
find MCP automation opportunities in your workflow
design parallel vs sequential workflow
score a task's agent-readiness
define human-in-the-loop checkpoints
assess agent risk
decompose work into sub-agents
build a SKILL.md
stress-test a skill
tune the skill description for triggering
which tasks → Skills (vs Projects/GPTs) + MCP deps
iterate + upgrade a skill
map the agent's graph logic
edit in the canvas paradigm
define the agent's tool use
find MCP opportunities
audit an agent run post-mortem
stress-test the agent's logic
design the human checkpoints
architect an agent for a task
generate the SOP the agent runs
Claude Project + connectors + memory accountability
Prompt 2: The Goal Command Center Setup
Pattern: Ecosystem Configuration
Claude is an ecosystem. With Projects, Memory, and Connectors, it becomes a system that sees your real life. This prompt configures your goal command center.
<context>
My primary goal: [YOUR GOAL]
The metric that shows progress: [HOW YOU MEASURE SUCCESS]
My tendency when I fail: [EXCUSES, AVOIDANCE, RATIONALIZATION?]
What I need from accountability: [DIRECTNESS, ENCOURAGEMENT, TOUGH LOVE?]
Tools where my goal-related activity lives:
- Calendar: [GOOGLE CALENDAR, OUTLOOK, ETC.]
- Documents: [GOOGLE DRIVE, NOTION, ETC.]
- Communication: [GMAIL, SLACK, ETC.]
</context>
<task>
Configure a Claude Project called "Goal Command Center" that transforms Claude into an accountability system connected to my real life. Include:
1. Project description and custom instructions that establish the accountability dynamic
2. Which connectors to enable and WHY (so Claude can verify, not just ask)
3. Memory instructions so Claude tracks this goal across weeks and months
4. How Claude should respond when it sees gaps between my stated intentions and actual behavior
5. A daily check-in format and a weekly review format
</task>
<constraints>
- Claude should verify claims against connected tools when possible ("You said you'd block 2 hours - I can see your calendar")
- Never accept excuses without exploring the pattern
- Must include recovery protocol for missed check-ins
- Balance supportive and honest (not harsh, not a cheerleader)
</constraints>
Tip: Enable Calendar and Drive connectors at minimum. The power is in Claude seeing your actual schedule and output, not just hearing your self-report.
Going deeper: Go to Settings > Connectors in Claude.ai to see all available integrations: Notion, Asana, Linear, Canva, Figma, and more. Each connector you add gives Claude more visibility into your actual work. If you have Claude Desktop on macOS, Cowork lets Claude work directly with your local files to complete multi-step tasks.a Claude Skill to remove goal friction
local research agent that saves a summary file
don't automate the wrong thing
find AI-coordination 10x goal versions
would this have seemed absurd in Jan 2024?
architect agents for the goal
first 48-hour action plan
deploy an agent that earns
turn an SOP into an agent-runnable schema
generate ready-to-use MCP use cases
evaluate whether something is a true agent
deploy your methodology as a Claude Project
pick the right first agent problem
scope a single agent (input/process/output/verify)
assess agent production readiness
build a human-in-the-loop workflow
Python collects/processes → AI API → output
learn Python fast for AI use
what Python to learn first
scrape data with Python
automate a business process
app idea → functional spec for no-code build
diagnosis + 3 fix strategies + nuclear option
small verifiable steps with if-it-fails branches
5 questions → one-page PRD before you build
master prompt including working example code
most boring, AI-friendly, well-documented stack
AI picks your first starter project
phrases that keep a long project as one whole
5-phase build with check-ins between phases
request data+narrative / analytic+intuitive views
operating rules/sequence/gates for all agents
analyze vs the goal
messy statements to normalized data
report insights
categorize transactions
coach, runs last
Claude breaks down + schedules + writes tasks to Todoist
review completed tasks + 3 improvements
proactive overdue/blocked/stalled → top-3 priorities
one-shot build a local kaizen task-board web app
run the team + refresh dashboard
shared state file for the agent team
five agent definitions
PostToolUse run formatter
PreToolUse block env/secrets changes
Stop sound/notification on finish