i. Five dimensions, ranked moves
Readiness scorecard.
Where you stand on engineering, data, leadership, product, and risk. Three to five concrete moves per dimension, sequenced by leverage. On file, defensible to a board.
We help companies build with AI, train their teams, and advise their leaders.
&
i. What we do
We are a senior-led AI consultancy
for engineering and operations.
We partner with leading companies to embed AI at the core of their engineering and their business operations: production AI features in the product, and internal tools that level up how finance, legal, marketing, and ops teams work. From strategy through delivery, same rigor across two domains.
We work best with ambitious teams in complex, regulated environments. The result is real ROI you can point to: senior engineers in production, decisions on record, internal tools your teams own end-to-end, and the people who can run what comes next.
ii. Services
How we work.
sive De practica · three orbits, four engagements
i. Strategia
Strategy.
Senior-led advisory inside your team. We sit beside your leaders and engineers, set direction together, and turn AI ambition into the decisions, hires, and architecture that make it real. Most engagements open with a five-dimension readiness benchmark.
- AI Readiness Benchmark· 1 week
- Embedded advisory· 3–6 months
iii. The Goldenberry difference
Engineered for outcomes.
- i.
Senior-only delivery. The person on the contract is the person doing the work. No junior leverage model, no agency-style staffing pyramid. Faster decisions, higher quality, less rework.
- ii.
Two clients at a time. Your team gets full attention, not a slice of it. No portfolio splits, no context-switching across six concurrent engagements. The people you meet on day one are the people doing the work on day ninety.
- iii.
Outcomes, not hours. Every engagement is anchored to a business outcome, not activity metrics. We measure success by impact on your business, not hours logged. Real ROI you can point to, not a delivery report.
- iv.
The deliverable is your team. Documentation, decisions on record, and engineers who can run the next AI initiative without us. We build on open foundations and battle-tested patterns, so what your team owns after we leave keeps shipping.
iv. From the field
Notes from the work.
Patterns we see often enough to write down. Excerpts below; the full essays sit in the articles index.
On scoring readiness
The score is a side effect. The action list is the deliverable.
A five-dimension framework for AI readiness
Field note · 9 min
On exhausted teams
The mandate from above is real. The exhaustion below is real. Both are pointing at the same fact.
The board wants AI. The team is exhausted. Now what
Field note · 4 min
On week one
There is no discovery phase. There is no kickoff deck. Week one is shipping week.
How we structure a 12-week AI engineering engagement
Field note · 8 min
On senior engineers
The juniors picked it up in days. The mid-levels in a couple of weeks. The seniors took two months.
Why senior engineers are the hardest to upskill on AI
Essay · 12 min
¶
v. What we leave behind
On your team’s desk.
We don’t leave a deck. We leave the things a team needs to keep shipping AI without us in the room.
ii. ADRs, the alternative, the reason
Architecture decisions, on record.
Every call we made, the option we rejected, and the reason. Reviewable six months later by an engineer who wasn't in the room. Reversible without archaeology.
iii. Runbook, evals where it matters, cost model
Features in production.
Live for real users, with the scaffolding that keeps them live: failure modes documented, evals where models are involved, tests where they aren’t, costs you can plot against revenue.
iv. Curriculum, hiring profile, playbook
The patterns your team owns.
A training curriculum your team can re-run for the next cohort, a hiring profile for the next AI-capable engineer, and the working patterns to run the next initiative without us.
vi. What we ship
Pace
pace.tools · open source · Apache 2.0
An AI specialist for every team.
Why we built it
After eighteen months of working with companies on AI engineering, the same gaps kept showing up. Engineering had a working AI tooling story. Sales, finance, legal, marketing, operations did not. Most were running private experiments in chat windows that nobody could repeat, review, or hand to a new hire.
The gap wasn’t model capability. The models could already do the work. The gap was context: the right skills, the tools they already use, and the working patterns that good teams arrive at on their own, eventually. We wrote those patterns down.
Pace is the framework that came out of it. It draws on the best workflows we’ve seen inside clients, generalised so any team can run them on day one. Free, open source, owned by the people using it.
One install per team
- Sales
- Marketing
- Engineering
- Data
- Product
- Finance
- Legal
- Operations
- People
- Customer Support
- Productivity
- Design
# Three lines and you’re in.
$ claude plugin marketplace add GoldenBerry-SO/Pace
$ claude plugin install sales@pace
$ /sales:call-prep Acme Corp
Works with Claude Code, Cursor, Codex, Gemini, and Copilot.
§
vii. A note from a client
“Goldenberry embedded with us for four months. They ran our AI architecture reviews, coached our two staff engineers, and helped us ship our first production AI feature with confidence. Six months after they left, we shipped three more without them.”
Yara P. · CTO, Berlin B2B SaaS · 80-engineer team
§
Build with AI. Ship with confidence. Let’s talk.
If you’re under pressure to modernise product delivery, lift productivity across finance, legal, marketing, or ops, or embed AI safely into core systems, we’d like to hear what you’re working on. The first 30 minutes are a working session, not a pitch. You walk away with a ranked next move whether or not we end up working together.
Book a 30-min working session →