About
Independent consultancy, led by Sophie Jonsson.
Four years inside Google Cloud's AI go-to-market teams, preceded by AI startup GTM and enterprise sales at Oracle. Now I make complex B2B marketing clearer to buyers and easier for teams to run.
I spent four years embedded in Google Cloud's AI GTM teams, working across Gemini, Workspace AI and Agentspace. Before that, I took go-to-market from zero at an AI robotics startup and worked in enterprise sales at Oracle.
That background matters because AI adoption is not a tool rollout. The system has to fit the buyer journey, the team's incentives and the evidence sales can use. A technically impressive workflow that ignores those constraints becomes another abandoned pilot.
Twegs is an independent B2B product marketing and systems consultancy. I improve what buyers experience through executive narrative and website builds, and how the team works through content workflow automation and market intelligence systems. Every engagement has a fixed scope and ends with approved work, a clear owner and a practical handover.
- Google Cloud
- Four years in AI go-to-market across Gemini, Workspace AI and Agentspace
- AI robotics
- Go-to-market built from zero at an AI startup
- Oracle
- Enterprise sales experience before moving into product marketing
- Twegs
- Independent B2B product marketing and systems consultancy
Positions
Working principles.
The assumptions behind the way engagements are scoped and run.
- 01
Diagnose the buyer journey, not one department at a time.
Marketing and sales can both report a good quarter while revenue misses. The useful unit of analysis is the path from first touch to closed deal, including the handoffs between teams.
- 02
Most AI work in the commercial function should reduce your tool count.
The default assumption is that adoption means procurement. More often the highest-return move is consolidating overlapping systems and connecting what remains properly.
- 03
Fix quality before automating volume.
Content and outreach are easy to scale. If targeting, positioning or qualification is weak, automation only increases the amount of poor work in circulation.
- 04
Customer-facing automation needs a named owner.
A person needs the authority to reject output, change the rules and stop the system. A generic review process is not enough.
- 05
Attribution is degrading, and pretending otherwise is expensive.
Consent gaps, dark social and AI-mediated research have broken the model most dashboards still assume. Self-reported attribution plus incrementality tests beat a confident, wrong model.
- 06
The handover is part of the work.
Every engagement ends with named owners, documentation and training. The project shouldn't create a need for permanent outside support.
Start with the operating problem.
Describe the unresolved argument, broken buyer journey, repetitive content work or missed market signal. I will tell you which build, if any, is the useful next step.