Raven Howard
Inquisitive, engaging, and always building the system.
Six years at Vendr, inside how enterprise software actually gets priced, sold, and bought. Home is Charleston, SC, where my wife and I are raising three boys. I work remote, and I’m looking for the next team worth building with.
The short version
I have sat on both sides of the table
Six years at advising some of the fastest-growing companies in the world as they bought nearly every kind of software there is. A decade of selling before that. Hover either side.
Hover a circle, or jump straight in.
Sells
Buys
Both chairs, one result
What the people in the room said
“Customers love Raven and how far he goes to get them the best outcome possible. He has been a mentor to many, constantly finding ways to level up everyone around him.”
Teammate · company-wide Slack“He saved them $4M on their Datadog renewal. They started skeptical of our ability to make an impact; by the end they were sold, and Raven was a huge driver behind that shift.”
For scale: the customer is a public company whose operating income runs nine figures a quarter. The $4M equaled roughly 3% of it. Drawn from their public earnings; the name stays out of it. Colleague · enterprise account“Hats off for returning 11× the savings guarantee on a first engagement.”
Vendr backed its fee with a savings guarantee. This engagement cleared that bar eleven times over. Colleague · deal announcement“Highly organized and supportive. This is what we’re paying Vendr for.”
Enterprise customer“Can more of our work be assigned to Raven?”
A customer, requesting him by nameAll-time deal-volume leader at the time of recognition: 520 closed deals at ~18% average savings.
The count kept climbing. He finished his career past 1,000. Internal recognition · VendrCondensed from company Slack and written customer feedback; colleagues and customers unnamed on purpose.
How I earned both chairs
Curiosity got me here. Systems keep me here.
I collect and connect: CliftonStrengths files it under Input and Ideation. It is how one person ends up fluent on both sides of the table, and why the fixing instinct always ends in a system.
Where the systems instinct goes
See a problem twice, build the system once
I led AI enablement across my team, then built and deployed , an internal tool that broke down complex contracts and pricing. A two-hour analysis became about fifteen minutes.
I used to be the friend who always knew the newest app before you did. Somewhere along the way I stopped waiting for other people to build them.
Now I build my own tools, apps, and agents, with real depth in context engineering, MCP, CClaude Code and
XCodex. MCP is not a party trick for me: I have written servers for Training Stack, Presence, and the recipe system, and my daily life runs through a dozen-plus connectors, from church finance in Ramp and Gusto to calendars, groceries, and yes, the coffee machine. Beyond the agents it is mostly open-source tools, self-hosted where that makes sense: .
The rest of the shelf · all mine, all running
Where I go deep
Most of a thousand deals sat in infrastructure
Four domains where I know the pricing models, not just the vendor names. Infrastructure is where I have spent the most time on purpose: it is the most complex spend a company carries, and usually the highest-value negotiation in the book. FFinOps Certified Practitioner.
Cloud
Committed-use deals, egress, and the discount mechanics behind each one.
AWSObservability
Where per-host, per-GB, and per-seat models quietly diverge from usage.
Data infrastructure
Consumption pricing, credits, and what actually drives the bill.
LLM and AI
Pricing still being invented, and most buyers have no reference point yet.
BedrockPublished thought leadership
- Ask which model is under the hood, and whether you already have access to it.
- Usage pricing: trial first, pay as you go, and never commit to volume without data.
- Ignore the bells and whistles. Does it improve what you do, or unlock something new?
- Know how optimized your instances are now versus how optimized they could be.
- Projected usage is the biggest lever in a discount negotiation. Project conservatively, then grow into the incentives.
- Get them to tell you no several times before you accept the wall.
- "Non-negotiable" is rarer than reps claim. Stay skeptical.
- Deadline pressure? Ask what happens if you sign the next day.
- Supplier and pricing analysis across the categories I negotiated every day: cloud, observability, data.
- The report runs on benchmarks from thousands of real transactions, the same data I worked from at the table.
Outside the job
The other rooms I help lead
Away from work I help lead a Charleston church community. I run its finance and HR operations, which has meant migrating Bill.com to RRamp, Rippling to
GGusto, and helping negotiate a roughly $3M building purchase.
I am Vice President of my neighborhood association in Charleston: I keep the contact list and meeting notes, send the reminders, and coordinate with city officials on behalf of my neighbors, from Councilman Keith Waring and Mayor William Cogswell to our local police commander.
I also speak most weeks to a room of about 600, so a room with a skeptical CFO feels familiar rather than frightening. It is the same skill.
What I am looking for · Remote from Charleston
Roles I would be excited about
Hover a role and watch which parts of my history light up. Click one for the story. The point of the graph: the evidence overlaps, so no single title boxes it in.
Let's talk
Pick whichever one is true. Each opens an email that is already written, so you only have to add the part I cannot guess.