Chapter 6
The Five Tangles in the Chain
Most Projects Fail From Predictable Mistakes
You have a roadmap showing Sam's merge automation is Priority 81—the clear #1 target.
You have a complete Decoupling Blueprint spec'ing exactly how to break it: AI consolidates the three platform exports, Sam reviews in 5 minutes instead of manually merging for 4.5 hours.
You're ready to build.
But here's what kills most automation projects:
Not bad technology.
Not lack of budget.
Not even resistance to change.
Five predictable mistakes that corrupt the roadmap before you even start building.
These tangles appear in every industry, every company size, every automation initiative. They're not unique to your situation. They're universal patterns.
A SaaS company spent 8 months mapping every process before building anything. A construction firm scored judgment-heavy work as "fully automatable" and built automations nobody would use. A professional services firm let the loudest executive override the priority formula and built the wrong thing first.
This chapter shows you the five tangles—and how to avoid them.
Mapping Everything Before Acting
The mistake
"Before we automate client reporting at Apex, let's map every process the agency does. Monthly reports, quarterly business reviews, campaign setup workflows, client onboarding, invoice generation, media buying negotiations, creative production, QA reviews..."
Six months later: Complete process documentation library. Fifty Flowcharts covering every corner of agency operations. Zero automations built. Sam still manually merging CSVs every Monday. Team exhausted from endless mapping sessions.
Why it fails
Analysis paralysis:
Perfection becomes the enemy of progress. "We can't prioritize until we understand the complete picture. We need to see how everything connects."
Overwhelming complexity:
You can't see the signal in the noise. Which of these 47 mapped processes should you actually automate first? Without signal counting, you're guessing.
Lost momentum:
Team stops believing anything will change. "We've been in mapping workshops for 6 months. When do we actually DO something? When does Sam get relief?"
Outdated documentation:Processes change during the mapping. By the time you finish documenting everything, half of it is already wrong. TechVantage added TikTok to their channel mix. The campaign setup process changed. Your 6-month-old maps are obsolete.
The fix
Map ONE critical outcome. Decouple the worst weak link. Measure the impact. THEN map the next outcome.
For Apex Media Partners:
Weeks 1-2: Map client reporting, identify merge as Priority 81, create Decoupling Blueprint
Weeks 3-8: Build and deploy automation, measure results
Week 9-10: Document learnings, celebrate win with team
Weeks 11-12: Map campaign setup process (next pain point team identified)
Build the muscle. Learn by doing. Iterate.
One outcome at a time. One weak link decoupled, measured, learned from. Then repeat the framework on the next outcome.
How to recognize you're in this tangle
Warning signs:
You've been "mapping processes" for >8 weeks with nothing built
Team meetings are about documentation and diagramming, not automation results
You have beautiful Flowcharts but no working automations
Someone says "We need to finish mapping everything before we can prioritize which to automate"
Executive asks "When will we see results?" and answer is "After we complete the mapping phase across all departments"
Team is fatigued from workshops but sees no tangible change
Recovery move
Stop mapping. Pick ONE outcome RIGHT NOW.
Ask your team: "Which single outcome causes the most pain today?"
For Apex: Client reporting (67.5 Media Buyer hours monthly, Sam/Jeremy/Steven all complain every Monday)
Map THAT outcome only. Create the deliverables:
Outcome Map (Chapter 1 process)
Weak Links Reveal (Chapter 2 process)
Weak Links Decoupling Roadmap + Decoupling Blueprint (Chapters 3-5 process)
Decouple the #1 weak link.
Ship in 6 weeks.
Say this to your team: "We'll come back to map campaign setup and other outcomes after we prove value with client reporting. One outcome. One win. Then we repeat the process."
Not: "After we finish mapping our entire operation, we'll create a comprehensive transformation roadmap and then decide what to automate first based on the holistic view."
This tangle appears everywhere
Marketing Agency: Tries to map reporting, campaign setup, media buying, invoicing, client onboarding, creative production all at once → 4 months of workshops, nothing shipped, team cynical
SaaS Company: Maps customer success, sales operations, support ticketing, product development, finance close processes → 6 months, incomplete documentation, team burned out
E-commerce: Documents inventory management, order fulfillment, returns processing, customer service, email marketing → 5 months, 40 process maps, zero automations
Construction: Maps pay apps, RFI workflows, change orders, project scheduling, procurement, safety compliance → 7 months, frustrated Project Managers still doing manual work
Pattern: Scope explosion kills momentum. One outcome mapped and automated beats fifty outcomes mapped and nothing automated.
Dismissing Complaint Signals as "Not Data"
The mistake
"Sam saying 'I HATE the merge' is subjective. We need objective metrics. Let's commission time studies across the Media Buyer team. Survey all stakeholders. Analyze historical platform export logs. Hire consultants to conduct comprehensive process efficiency analysis..."
Meanwhile, Sam has been saying "I HATE the first week of the month" every Monday morning for 18 months. All three Media Buyers echo the same complaint. Dismissed as "just venting" or "that's how agency life is."
Why it fails
Delays action:
Waiting for "better data" that often doesn't materialize or takes months to gather. Time study takes 6 weeks. Survey gets 30% response rate with inconclusive results. Meanwhile Sam is still drowning in VLOOKUP failures every Monday.
Misses the obvious:
Your team already knows what's broken. They live it every day. Sam knows exactly which step is painful (the merge). Jeremy and Steven confirm it independently. That's not noise—that's triangulated data.
Political:
"Objective metrics" can be gamed, debated, reinterpreted. "The time study shows 3.8 hours, not 4 hours—therefore not a priority." But complaint signals are harder to dismiss—someone said "I HATE this," you heard it, you counted it. That's objective signal counting.
Expensive:Time studies, stakeholder surveys, consulting engagements cost real money ($70-140K) and consume real time (6-12 weeks). Counting complaint signals costs a 40-minute team conversation.
The fix
Count complaint signals objectively.
When Sam says "I HATE this," that's a signal. Mark it.
When Jeremy says "Mondays are the worst," that's a signal. Mark it.
When Steven says "This is mind-numbing," that's a signal. Mark it.
When you see all three Media Buyers groan when someone mentions "first week of the month," that's a signal. Mark it.
Tally them up. 9 signals beats 5 signals. 5 beats 2. That's objective counting.
You're not ignoring data. You're treating complaint signals AS data—and they're faster, cheaper, and more accurate than commissioned studies.
How to recognize you're in this tangle
Warning signs:
Team saying "we need better data" despite clear, repeated pain points
Roadmap blocked for weeks waiting for survey results or time study reports
Someone says "Complaints aren't evidence" or "That's just perception, not reality"
Months passing with no action because you're "gathering objective metrics"
Recovery move
Do a 40-minute Complaint Audit instead of a 6-week study.
Gather Sam, Jeremy, Steven, Jordan, Morgan.
Go through your Outcome Map link by link:
"First link: Media Buyers export data from 3 platforms. What do you complain about here? What breaks? Where does it wait?"
Listen. Mark signals. Count.
"Next link: Merge the CSVs..."
Sam: "UGH. Here we go. I HATE this part..."
Keep marking as they talk. The ranking emerges in 40 minutes.
Say this to stakeholders: "Our three Media Buyers all independently complained about the merge step—9 distinct pain signals total. That IS data. Triangulated, repeated, consistent across the team. Let's count those signals and act on them."
Not: "Let's conduct a comprehensive time-motion study and stakeholder survey to objectively quantify process inefficiencies across the reporting workflow with statistical significance."
Examples
Marketing Agency: Debates for 2 months whether "the merge is really the bottleneck," commissions time study → Could have just counted Sam/Jeremy/Steven all saying "I HATE this" in one team meeting (Week 1 vs Month 3)
SaaS: Surveys 100 CSMs about pain points, gets 40% response rate, data inconclusive on priorities → Could have asked the 8-person core CSM team "What do you dread doing weekly?" in 20-minute standup, gotten clear answer (health score calculations)
E-commerce: Hires consultant to analyze inventory process for $80K over 6 weeks → Could have asked Inventory Manager in 5-minute 1-on-1: "What takes longest and frustrates you most?" Answer: "Manual reorder calculations with outdated lead times, causes stock-outs"
Construction: Commissions time study measuring Project Accountant's activities for 4 weeks (invasive, disruptive) → Could have counted Tiffany saying "I dread month-end consolidation" and observed 15% error rate in one 10-minute conversation
Pattern: Overthinking validation delays action while the pain persists. Your team knows. Ask them. Count the signals. Move.
Wishful Thinking on RDS Scores
The mistake
Scoring Morgan's strategic deck review as R=3, D=3, S=3 (RDS = 9) because "AI is so advanced now with GPT-5 and Claude, surely it can understand client context and do strategic reviews."
Building "full automation" of Morgan's review process.
Deploying it.
Morgan refuses to use it: "This AI doesn't understand that TechVantage's board is pressuring them on brand metrics. It recommended pausing brand campaigns based purely on ROAS data. That would destroy our relationship. I can't approve this."
Automation fails. $73K and 8 weeks wasted. Trust in the framework collapses. Team says: "See, this AI automation stuff doesn't work for real strategic work."
Why it fails
Overpromising:
Claiming AI can do things it fundamentally cannot—contextual judgment requiring relationship knowledge, strategic synthesis requiring business understanding, nuanced decision-making requiring unstated context.
Wasted effort:
Building automation that doesn't work wastes time, budget, and team goodwill.
Lost trust:
Team stops believing in the framework: "We tried to automate strategic review and it failed. This whole RDS thing doesn't work."
Expensive failures:Sunk cost on wrong automations (RDS scored too high) means less budget available for RIGHT automations (actual RDS 9 links like Sam's merge).
The fix
Be conservative when scoring RDS. When in doubt, score LOWER.
Morgan's review should be scored honestly:
R = 1 (every review contextually unique—TechVantage needs different strategic lens than Client B)
D = 2 (some guidelines exist—"addresses client goals"—but applying them requires judgment about what those goals really mean)
S = 1 (not safe to delegate—$800K annual contract, wrong strategic direction damages client relationship)
Total: 4/9 → Keep human, AI assists at most
Better to be pleasantly surprised by automation potential than disappointed by failed builds.
If you're debating between scoring something a 2 or a 3, score it a 2. Conservative scoring protects you from wasted effort.
How to recognize you're in this tangle
Warning signs:
RDS scores are almost all 7s, 8s, and 9s (suspiciously high—some work should be human)
Team is skeptical when you present scores: "Really? AI can do Morgan's strategic review?"
Building "full automation" of judgment-heavy, relationship-heavy, or strategy-heavy work
No links scored below 5 (unrealistic—not everything is automatable)
Defending high scores with "AI is really advanced now" instead of honest assessment of repeatability/definability/safety
Scoring based on future AI capabilities ("GPT-6 will be able to...") instead of current reality
Recovery move
Re-score conservatively. Apply the reality-check questions:
For each dimension:
Repeatable (R):
"If I trained a brand new hire on this task, how long would training take?"
1 day with a checklist → Score 3
1 week with examples and coaching → Score 2
6 months of apprenticeship → Score 1
Definable (D):
"Would two people independently checking this always agree on pass/fail?"
Yes, always (it's factual) → Score 3
Sometimes disagree (some judgment required) → Score 2
Often disagree (it's contextual) → Score 1
Safe (S):
"If this went wrong and reached a client/customer, what happens?"
Internal redo, annoying but no external damage → Score 2-3
Client sees error, relationship strained → Score 1
Could lose the account or revenue → Score 1
If you have ANY doubt, go lower.
Sam's merge: "Could a new hire do this from a checklist? Yes → R=3. Is 'correct' factual or opinion? Factual → D=3. If wrong, can we catch it internally? Yes → S=3." Clear RDS 9.
Morgan's review: "Could a new hire do this from a checklist? No, needs months of client relationship knowledge → R=1. Is 'good review' factual or judgment? Judgment → D=2 at best. If wrong, does it reach client? Yes, damages relationship → S=1." Clear RDS 4.
Common over-scoring mistakes
"Reviewing for quality" → Often scored 7-9, should be 4-5 (requires judgment about what "quality" means in context)
"Writing client-facing content" → Often scored 7-9, should be 5-6 (AI can draft structure, human refines for tone/context)
"Deciding priorities" → Often scored 5-7, should be 3-4 (context-dependent judgment about trade-offs)
"Building relationships" → Sometimes scored 4-5, should be 3 (keep human, relationship work is fundamentally human)
Pattern: Wanting automation to work doesn't make it work. Score based on honest assessment of repeatability, definability, and safety—not on wishes or AI marketing claims.
Politics Override Priority Formula
The mistake
The Priority Formula says: Decouple Sam's merge first (81 points).
But the Creative Director says: "I want deck creation automated. That's what's really slowing us down. Jordan spends an hour per client on PowerPoint formatting—that's 15 hours a month. Let's do that first."
Leadership agrees: "Creative Director has a point. Let's automate deck creation."
Team builds deck automation (Priority 14: 2 pain signals × 7 RDS).
It delivers minor value—saves Jordan 30 minutes per client on screenshot formatting.
Meanwhile, Sam's merge weak link (Priority 81) remains manual. Sam still manually matching 119 campaigns with VLOOKUP failures every Monday. 4.5 hours per client. 67.5 hours monthly. The screaming weak link persists.
Why it fails
Building the wrong thing:
Not attacking the biggest pain point means the biggest problem persists. Sam, Jeremy, Steven still suffering.
Wasted resources:
Time and budget spent on low-priority item (deck creation: 14 points) that doesn't move the needle significantly.
Misses the real pain:
Sam's merge pain (9 signals, 4.5 hours, 67.5 hours/month scaled) continues. Team morale doesn't improve because the worst weak link is still there.
Political dysfunction:
Undermines the entire framework. If priority scores don't matter when executives disagree, why did you spend time calculating them objectively?
Team demoralization:Sam sees leadership ignore the data (merge: 81 points) and prioritize based on who speaks loudest in the meeting (Creative Director's preference: 14 points). Message received: "My pain doesn't matter."
The fix
Trust the math. Make the formula politically defensible.
Priority = Pain Signals × RDS Score
81 beats 14. That's not opinion. That's arithmetic.
When Creative Director pushes for deck automation, show the scoring:
"Deck creation scored:
2 pain signals (Jordan said 'tedious formatting' once)
× 7 RDS (it's automatable)
= 14 priority
Sam's merge scored:
9 pain signals (Sam, Jeremy, Steven all said 'I HATE this,' plus VLOOKUP failures, blocks downstream work)
× 9 RDS (perfectly automatable)
= 81 priority
The math says merge first. That's 5.7× higher priority. We'll address deck creation in Phase 2, but we attack the 81-point weak link before the 14-point weak link.
If someone wants to override, ask: 'Can you show me why deck creation should score higher than 14? Did we miss complaint signals or underestimate the RDS?'"
The formula protects you from politics.
How to recognize you're in this tangle
Warning signs:
Executive pushing to automate something that scored <20 priority
Team building based on "who's loudest" or "who has the CEO's ear" instead of objective ranking
Roadmap changed from original priority order without re-scoring the links
Someone says "I know the formula says X, but I really think we should do Y because..."
Executive says "Just do my team's automation first, we can do the others later"
Priority scores presented once, then ignored in decision-making
Recovery move
Re-present the priority scores in a stakeholder meeting. Make the data visible.
Show the full ranking. Explain the formula clearly.
"Here's what the objective data shows us. Sam's merge: 81. Deck creation: 14. That's a 5.7× difference in priority.
If someone disagrees with the priority ranking, let's re-score together. Let's count the complaint signals for deck creation again. Let's evaluate the RDS honestly.
But we shouldn't override the math without changing the inputs. The formula exists to prevent 'whoever's loudest wins' decision-making."
Make it socially awkward to ignore the data.
If Creative Director insists:
"Okay, let's re-examine the signals. Deck creation—how many people complained about it?"
CD: "Well, Jordan mentioned it's tedious..."
"That's 1 complaint signal. Sam's merge has 4 complaint signals from three different Media Buyers saying 'I HATE this.' Plus 3 breakage signals. Plus 2 waiting signals. Total: 9.
Can you explain to the team why we should prioritize the 1-signal link over the 9-signal link?"
Use the framework to force honest conversation.
Most executives back down when the math is clear and public. They don't want to be seen overriding objective data for political reasons.
Common political override patterns
"Automate my team's weak link" (executive says) → But their team scored 18 priority, another team scored 54
"Automate the visible thing" (looks good in board meeting) → But visibility scored 20, invisible weak link scored 65
"Automate the easy thing" (low technical risk) → But easy thing scored 35, harder thing scored 72 (attack the jackpot even if technically harder)
"Automate what I understand" (executive knows that process intimately) → But familiar process scored 22, unfamiliar process scored 58
Pattern: Squeaky wheel (loudest executive) gets the grease → Wrong wheel gets greased, squeakiest wheel (actual worst weak link) still squeaking.
Counter-pattern: Show the math publicly. Make override politically costly.
Spec Paralysis
The mistake
The Decoupling Blueprint for Sam's merge starts at 4 pages (reasonable).
Then someone asks: "What if Google Ads API goes down mid-process?"
Add 2 pages on API failure handling, retry logic, fallback procedures.
"What if TechVantage changes campaign names mid-month?"
Add 3 pages on detecting mid-cycle changes, reconciliation logic, notification procedures.
"What if Meta changes their metric definitions?"
Add 2 pages on schema versioning, backward compatibility, migration paths.
"What if Sam is on vacation when AI flags an issue?"
Add 2 pages on backup reviewer assignment, escalation procedures, notification hierarchies.
"What if we need to support TikTok and Pinterest next year?"
Add 4 pages on extensibility architecture, plugin framework, new platform integration procedures.
"What if campaign data includes international spend in different currencies?"
Add 3 pages on currency conversion, exchange rate handling, multi-currency validation.
Three months later: The Decoupling Blueprint is 47 pages. Still defining requirements for edge cases that have never actually happened. Nothing built. Sam still manually merging every Monday.
Team frustrated: "We're overthinking this. Can we please just ship something?"
Why it fails
Perfect is enemy of shipped:
Trying to handle every conceivable edge case upfront means never shipping. You're solving theoretical problems instead of the real problem (Sam's 4 hours of manual merging).
Complexity explosion:
Every "what if" adds code paths, testing scenarios, and development time. An 8-week build becomes a 20-week build. Scope balloons.
Lost focus:
The core use case (handle TechVantage and the 14 other similar clients with standard Google + Meta + LinkedIn structure) gets buried under edge case handling for scenarios that might never occur.
Delayed value:Nothing ships while you're perfecting the spec for hypothetical situations. Sam is still doing manual work. The pain continues.
The fix
Spec the 80% core use case. Ship it in 6 weeks. Handle edge cases AS THEY ACTUALLY COME UP.
For Apex's merge automation:
Core use case (handles 14 of 15 clients, ~93%):
Client has Google Ads + Meta + LinkedIn
Standard campaign structure (no exotic variations)
Monthly reporting cycle
Campaign names follow predictable patterns Sam demonstrated in examples
Ship this in Week 6.
Edge cases (defer to V2, add only if they actually become problems):
"What if client adds TikTok mid-year?"
→ V1: Flag for manual handling initially (Sam can manually add TikTok data to the consolidated file in 15 min)
→ V2: Add TikTok support in Month 6 if 3+ clients adopt TikTok (only build if it's actually needed)
"What if API goes down?"
→ V1: Send Red email to Sam, she falls back to manual merge (4.5 hrs, but rare
→ V2: Add retry logic and API monitoring in Month 4 if downtime becomes frequent issue (only build if it's actually a problem)
"What if campaign names change mid-month?"
→ V1: AI uses campaign list from Month 1 export (slight lag acceptable)
→ V2: Add mid-cycle change detection in Month 6 if clients complain about lag (only if actual feedback requires it)
Keep the Decoupling Blueprint to 5 pages maximum. Everything else goes in a "Future Enhancements To consider" section.
Ship V1 core use case. Learn from real usage. Iterate based on actual needs, not hypothetical fears.
How to recognize you're in this tangle
Warning signs:
Decoupling Blueprint exceeds 5 pages and still growing
Team debating "what if [rare scenario that's never happened]" for hours in spec meetings
No clear "we're done spec'ing" definition—always one more edge case to consider
Someone says "We can't ship until we've handled the TikTok scenario" (even though zero clients use TikTok)
Spec includes phrases like "comprehensive," "future-proof," "enterprise-grade," "handles all scenarios"
Build timeline keeps extending: "Need 2 more weeks to finish the spec"
Recovery move
Ask: "What's the core use case that handles 80% of our actual current usage?"
For Apex merge automation:
Core: 15 clients, all have Google + Meta + LinkedIn, standard campaign structures, monthly cycle
Handles: 14-15 clients (93-100% of current workload)
Spec and ship THAT. Cut everything else.
Reduce the Decoupling Blueprint back to:
Current weak link state: 1 paragraph
Target decoupled state: 1 paragraph
How it works (core use case only): 1-2 pages
Expected impact: 1 paragraph
Total: 5 pages maximum.
Edge cases get ONE short section at the end:
"Future Enhancements To consider (Build if needed based on real usage)"
TikTok/Pinterest support (if clients adopt these platforms)
Mid-cycle campaign changes (if lag becomes issue)
Multi-currency handling (if international clients added)
Ship V1 in Week 6. Add enhancements in Months 4-6 only if real usage shows they're actually needed.
Common spec paralysis triggers
"What if the data source changes format?"
→ V1: Detect format change, send Red email to Sam, she investigates (happens rarely)
→ V2: Auto-adapt to minor format changes (build if Google/Meta frequently changes export structure—hasn't happened in 2 years)
"What if we need to support 10 more ad platforms?"
→ V1: Support the 3 platforms that represent 95% of current spend (Google, Meta, LinkedIn)
→ V2: Add TikTok/Pinterest/etc. as clients actually adopt them (build when needed, not speculatively)
"What if Media Buyer is on vacation when AI flags issue?"
→ V1: Email sits in their inbox until they return, they review when back (this is fine for 1-week vacation)
→ V2: Backup reviewer auto-assignment (build only if vacation coverage becomes actual problem)
Pattern: Solve the real problem you have today (Sam's 4.5-hour manual merge). Don't solve hypothetical problems you might have someday (TikTok support when zero clients use TikTok).
The Pattern Across All Five Tangles
They all share the same root cause: Fear of imperfection.
Mapping everything = fear of missing something important if you only map one outcome
Waiting for "better data" = fear of acting on imperfect complaint signals instead of "objective" studies
Optimistic RDS scoring = fear of admitting AI's current limits
Political override = fear of disagreeing with executives or saying "no" to the loudest voice
Spec paralysis = fear of edge cases breaking in production
The antidote to all five: Ship imperfect. Learn fast. Iterate.
Perfect never ships.
Good-enough ships in weeks and improves based on real usage.
For Apex:
Map ONE outcome (client reporting), not all 47 agency processes
Count Sam's complaints AS data, don't wait for time studies
Score Morgan's review conservatively (RDS 4, keep human)
Trust the Priority 81 score, don't let politics override
Spec the core use case (5 pages maximum), not every edge case (47 pages)
Ship the merge automation in Week 6. Learn from Weeks 9-12. Iterate in Month 4-6 based on actual usage patterns.
Your Tangels Checklist
Ask yourself before you start building:
Are we tangled in any of these patterns?
Tangle 1 - Mapping Everything:
□ Have we been mapping/analyzing for >8 weeks without building anything?
□ Are we trying to map multiple outcomes before decoupling even one weak link?
□ Is the team asking "When do we actually ship something?"
Tangle 2 - Dismissing Complaints:
□ Are we waiting for "better data" (time studies, surveys) despite clear repeated complaint signals?
□ Did someone say "Complaints aren't data" when the team clearly expressed pain?
Tangle 3 - Wishful RDS Scoring:
□ Are most of our RDS scores 7-9? (Suspiciously high—some work should be human)
□ Did we score judgment-heavy or relationship-heavy work as RDS 7-9?
□ Are we defending scores with "AI is advanced now" instead of honest repeatability assessment?
□ Are we scoring based on future AI capabilities instead of current reality?
Tangle 4 - Political Override:
□ Is someone pushing to build something that scored <20 priority while higher scores wait?
□ Did we change the roadmap order without re-scoring to justify it?
□ Is "who wants it most" driving decisions instead of "what scores highest"?
Tangle 5 - Spec Paralysis:
□ Is our Decoupling Blueprint >5 pages and still growing?
□ Are we debating edge cases that have never happened?
□ Is there no clear "spec is done" definition?
□ Has timeline extended beyond 8-10 weeks because we're still spec'ing?
If YES to ANY: You're tangled. Use the recovery moves from this chapter.
The recovery pattern is the same for all five:
STOP the tangling behavior.
(Stop mapping, stop waiting for studies, re-score honestly, show the math, cut the spec)
SHIP something small and real in 6 weeks.
(One outcome, one weak link, core use case)
LEARN from reality.(Measure results, iterate based on actual usage, add enhancements only if needed)
You know the tangles that kill automation projects. You know how to avoid them. Now understand what happens after you successfully decouple the first weak link.
