BNS Consulting | AI Companion for Engineering Leaders

From AI-curious to AI-shipping.

For engineering teams that have to keep delivering while they change.

I'm Sebastian Binder. Over the past decade I led cloud transformations at digital publishers, eCommerce platforms, and SaaS scale-ups. I now do the same work for AI, as a monthly advisor to the engineering leaders running it.

The Shift

In 18 months, AI moved from interesting to expected. Boards are asking about it. Engineers are experimenting with it. Most companies are in between. Not behind enough to panic, not ahead enough to see real benefit.

The tools work. Cursor, Claude Code, Copilot: solved problems. The unsolved problem is the organization around them. How code gets reviewed. Who owns what. What "senior" means now. Which roles to hire for next year. How to show the board it's actually working.

Done badly, the result is one of two outcomes. The first is AI theatre: everyone has a license, no one ships faster. The second is AI sprawl: each team rolls its own setup, no shared standards, twice the surface area to maintain. Both waste budget and trust.

Done well, the effect builds over time. Each quarter the team ships more with less churn. The gap to competitors who aren't doing this widens. Closing that gap is the work.

The Offer

AI Companion for Leadership

A monthly advisory retainer for CTOs, VPs of Engineering, and team leads driving AI adoption in their engineering organization.

Format: Monthly retainer with a regular 1:1 cadence and ad-hoc availability over Slack, email, or call. Engagement reviewed every quarter.
Includes: Strategy reviews. Decision support on tools, vendors, and policy. Briefings for board and team conversations. An outside perspective you can be candid with.
Outcome: You make decisions with better information. You're not the only person in the room who has already worked through them.
Not this: I do not run the rollout for you, manage your engineers, or sit between you and your team. The work stays yours; the thinking is shared.

Method

How the retainer unfolds over the first few months.

Assess

Where the team actually stands today. Tools in use, friction points, leadership stance. The basis is conversations and code, not survey software.

Align

Agree on what "AI-augmented" means for this team specifically. The target outcome, the guardrails, the parts of the work that stay with people. Leadership and engineering work from the same definition.

Decide

Work through the rollout decisions your team will execute: tool choices, workflows, review practices. You bring the org context. I bring twenty years of watching these decisions play out. Faster decisions because the trade-offs are already on the table.

Continue

The retainer continues as long as it adds value. We review every quarter whether to keep going. The team owns the work; I stay available for the next hard decision.

Background

Twenty years in production Linux and AWS. The last decade leading cloud transformations at digital publishers, eCommerce platforms, and SaaS scale-ups. The patterns of where transformations succeed and where they stall are fairly consistent. Knowing both sides is part of the work.

Background: AWS Solutions Architect, daily user of current AI tooling, former team lead who has trained both engineers and other leads. I work hands-on, not from a deck.

Case Studies

Real engagements. Client names withheld.

Digital publisher · ~80 engineers

Context: High-traffic news platform. Mixed seniority across teams. Strong delivery culture, inconsistent adoption of AI tools.
Challenge: Senior engineers running personal experiments. Junior engineers either blocked or pasting unsafe output. No shared review standard.
Approach: Advised the engineering leadership through a three-month rollout: tool selection, review guardrails, paired enablement with team leads.
Outcome: Active use by ~70% of engineers within 90 days. PR throughput +18%. Defect rate unchanged.

B2B SaaS scale-up · Series C

Context: Fast-moving product organization. CTO under board pressure to present an AI strategy.
Challenge: Engineering was making real progress, but leadership could not see it. Engineering felt micromanaged.
Approach: Four-month CTO advisory paired with shared team-enablement workshops. Closed the visibility gap without slowing delivery.
Outcome: Quarterly board updates delivered with two clear adoption KPIs. Engineer satisfaction +12 points over the engagement. CTO continued the retainer past the initial four months.

Enterprise IT modernization

Context: Mid-sized engineering organization in the middle of a cloud migration, considering AI rollout in parallel.
Challenge: Risk-averse leadership. Regulated data. Concern about running two transformations at once.
Approach: Worked with the leadership team to sequence the two transformations: stabilize the cloud migration first, run a tightly-scoped AI pilot in one team, then scale.
Outcome: Cloud migration completed within the original nine-month plan. AI pilot scaled from one team to three the following quarter. Zero compliance findings during the engagement.

Get in touch

Looking for someone to hand out Copilot licenses and call it done? This isn't that.

If you're a CTO or team lead working through how AI actually changes the way your team operates, and how to lead that change without breaking what already works: send a message.

Email sebastian @ bns-consulting.de

Location Rosenheim, Germany · Remote across DACH and EU