We find the bottleneck that's actually costing you time and money — then remove the smallest thing that fixes it.
Everyone sees six problems.
Diagnosis-first engagements — we find the actual bottleneck before we ever propose a fix.
See the philosophy →Short, practical PDF guides for operators who want a clear next move, not another framework.
Browse the series →AI is the fastest new line in every budget — and the easiest to get wrong. Here's how it earns its place.
Enter Practical AI →A 4-step guide to fixing what's actually broken — free when it launches.
During a finance and strategy seminar in business school, our team was assigned a famous Harvard Business School case study: Optical Distortion, Inc.
The case centered on a novel product — tinted, red contact lenses for egg-laying hens. In commercial poultry farming, aggressive pecking and cannibalism were major operational losses. Research showed that if a chicken's vision was filtered through a red lens, it couldn't distinguish the color of blood, neutralizing its territorial instincts.
The assignment was straightforward: determine the optimal go-to-market pricing strategy.
Our classroom spent an entire hour deep in the weeds. We built complex financial models, calculated amortized unit costs, debated supply chain friction, and factored in the labor required to manually insert tiny plastic lenses into millions of eyes.
Every time the professor introduced a new variable — changing feed prices, shifting mortality rates, competing debeaking techniques — we adjusted our spreadsheets and refined our margins.
Near the end of the session, a realization surfaced: putting a simple red light bulb in the chicken coop produced the exact same behavioral response.
No supply chains. No individual lens installation. No complex distribution models. Just an existing fixture and a cheap bulb.
It's remarkably easy to get so bogged down analyzing a hard problem that you miss the elegant, simple answer staring right at you. Expertise often creates blind spots — we default to over-engineering solutions instead of stepping back to see the whole picture.
We had spent an hour solving the wrong problem: "How do we price and distribute red contact lenses?" Had we defined the true underlying goal — "How do we filter a chicken's visual spectrum to alter its behavior?" — the range of solutions would have opened up instantly. Define the actual job, and you stop limiting your options.
We founded Red Bulb Strategies to be the team that steps back, challenges assumptions, and looks for the red bulb — the team that helps organizations cut through operational noise, reframe complex problems, and find high-impact solutions that are often hiding in plain sight.
Before we let you over-engineer a contact lens, we'll make sure you don't just need a better light bulb.
Whether it's a business bottleneck or an AI investment decision, the first job is always the same: define what's actually broken before spending a dollar on the fix.
Short, practical PDF guides for operators, founders, and ops leaders who need a clear next move — not another framework to file away.
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AI is the fastest-growing line item in every budget, and the easiest one to get wrong. Practical AI is the Red Bulb track for operators who want AI spend that actually changes outcomes — not a pilot that quietly disappears by Q3.
Same discipline as the core practice — find where AI actually changes your position before recommending a tool.
Straight talk on where the AI platform landscape is headed, and what it means for your roadmap.
See the offer →Practical, guide-format breakdowns you can act on without hiring a consultant.
Browse guides →Start wherever the risk is lowest for you — a short strategic read, or a diagnostic — and move up only once the last engagement proved itself.
A focused read on where AI is actually shifting your competitive position — and where it's just noise you're paying attention to for no reason.
$3,000–$6,000A light diagnostic on tooling, data posture, and skill gaps — a clear-eyed baseline before committing further.
$1,500–$3,000We shadow your team, map the real work, and hand back bespoke training, guides, and platform recommendations built around it — not generic AI 101.
$9,000–$18,000 / teamMoves teams from prompting to delegating — agentic tools for repeatable, multi-step work.
$15,000–$30,000Bespoke agents and integrations wired into your own systems, scoped project by project.
$25,000+Utilization check-ins — recurring pulse checks that confirm adoption is sticking and impact is compounding.
Typical elapsed time: 2–3 weeks (10–12 billable days), sized to a team of roughly 10–25. Larger rollouts run as parallel or sequential cohorts.
Align on target teams, success metrics, and access. The people being shadowed know exactly why — this is done for them, not to them.
1–2 daysWe sit with your people and watch the real work — tasks, tools, repetition, and the moments that eat the most time.
3–5 daysObserved tasks get mapped to real AI opportunities. We draft the training content, the guides, and the platform shortlist.
3–5 daysLive, bespoke training by role or team, plus written guides your people keep using long after we're gone.
1–2 daysPlatform recommendations and an expected cumulative impact estimate for leadership, plus a clear next step.
1 dayPricing above reflects flat package fees, not day rates — packaged pricing is easier to sell, matches how clients think about the problem, and rewards efficiency over hours billed. Founding-client pricing (roughly 20–30% off) is worth considering for the first 2–3 engagements in exchange for a case study and usable impact numbers.
Practical AI guides are in development using the same Business Decisions format — short, direct, and built to act on.
Leave your email and we'll let you know the moment the first Practical AI guide is live.